Password vaults are increasingly popular applications that store multiple passwords encrypted under a single master password that the user memorizes. A password vault can greatly reduce the burden on a user of remembering passwords, but introduces a single point of failure. An attacker that obtains a user’s encrypted vault can mount offline brute-force attacks and, if successful, compromise all of the passwords in the vault. In this paper, we investigate the construction of encrypted vaults that resist such offline cracking attacks and force attackers instead to mount online attacks. Our contributions are as follows. We present an attack and supporting analysis showing that a previous design for cracking-resistant vaults—the only one of which we are aware—actually degrades security relative to conventional password-based approaches. We then introduce a new type of secure encoding scheme that we call a natural language encoder (NLE). An NLE permits the construction of vaults which, when decrypted with the wrong master password, produce plausible-looking decoy passwords. We show how to build NLEs using existing tools from natural language processing, such as n-gram models and probabilistic context-free grammars, and evaluate their ability to generate plausible decoys. Finally, we present, implement, and evaluate a full, NLE-based cracking-resistant vault system called NoCrack.

We examine a FlipIt game in which there are multiple resources which a monolithic attacker is trying to compromise. This extension to FlipIt was considered in a paper in GameSec 2014, and was there called FlipThem. Our analysis of such a situation is focused on the situation where the attacker's goal is to compromise a threshold of the resources. We use our game theoretic model to enable a defender to choose the correct configuration of resources (number of resources and the threshold) so as to ensure that it makes no sense for a rational adversary to try to attack the system. This selection is made on the basis of the relative costs of the attacker and the defender.

Recently, several research groups in cryptography have presented new elliptic curve model based on Edwards curves. These new curves were selected for their good performance and security perspectives. Cryptosystems based on elliptic curves in embedded devices can be vulnerable to Side-Channel Attacks (SCA), such as the Simple Power Analysis (SPA) or the Differential Power Analysis (DPA). In this paper, we analyze the existence of special points whose use in SCA is known as Same Value Analysis (SVA), for Edwards curves. These special points show up as internal collisions under power analysis. Our results indicate that no Edwards curve is safe from such an attacks.

Protecting software from malware injection is the holy grail of modern computer security. Despite intensive efforts by the scientific and engineering community, the number of successful attacks continues to increase. We have a breakthrough novel approach to provably detect malware injection. The key idea is to use the very insertion of the malware itself to allow for the systems to detect it. This is, in our opinion, close in spirit to the famous Heisenberg Uncertainty Principle. The attackers, no matter how clever, no matter when or how they insert their malware, change the state of the system they are attacking. This fundamental idea is a game changer. And our system does not rely on heuristics; instead, our scheme enjoys the unique property that it is proved secure in a formal and precise mathematical sense and with minimal and realistic CPU modification achieves strong provable security guarantees. Thus, we anticipate our system and formal mathematical security treatment to open new directions in software protection.

Dividing last level caches into slices is a popular method to prevent memory accesses from becoming a bottleneck on modern multicore processors. In order to assess and understand the benefits of cache slicing in detail, a precise knowledge of implementation details such as the slice selection algorithm are of high importance. However, slice selection methods are mostly unstudied, and processor manufacturers choose not to publish their designs, nor their design rationale. In this paper, we present a tool that allows to recover the slice selection algorithm for Intel processors. The tool uses cache access information to derive equations that allow the reconstruction of the applied slice selection algorithm. Thereby, the tool provides essential information for performing last level cache attacks and enables further exploration of the behavior of modern caches. The tool is successfully applied to a range of Intel CPUs with different slices and architectures. Results show that slice selection algorithms have become more complex over time by involving an increasing number of bits of the physical address. We also demonstrate that among the most recent processors, the slice selection algorithm depends on the number of CPU cores rather than the processor model.

Frequent itemset mining is a task that can in turn be used for other purposes such as associative rule mining. One problem is that the data may be sensitive, and its owner may refuse to give it for analysis in plaintext. There exist many privacy-preserving solutions for frequent itemset mining, but in any case enhancing the privacy inevitably spoils the efficiency. Leaking some less sensitive information such as data density might improve the efficiency. In this paper, we devise an approach that works better for sparse matrices and compare it to the related work that uses similar security requirements on similar secure multiparty computation platform.

The traditional fault analysis techniques developed over the past decade rely on a fault model, a rigid assumption about the nature of the fault. A practical challenge for all faults attacks is to identify a fault injection method that achieves the presumed fault model. In this paper, we analyze a class of more recently proposed fault analysis techniques, which adopt a biased fault model. Biased fault attacks enable a more flexible fault model, and are therefore easier to adopt to practice. The purpose of our analysis is to evaluate the relative efficiency of several recently proposed biased-fault attacks, including Fault Sensitivity Analysis (FSA), Non-Uniform Error Value Analysis (NUEVA), Non-Uniform Faulty Value Analysis (NUFVA), and Differential Fault Intensity Analysis (DFIA). We compare the relative performance of each technique in a common framework, using a common circuit and using a common fault injection method. We show that, for an identical circuit and an identical fault injection method, the number of faults per attack greatly varies according with the analysis technique. In particular, DFIA is more efficient than FSA, and FSA is more efficient than both NUEVA and NUFVA. In terms of number of fault injections until full key disclosure, for a typical case, FSA uses 8x more faults than DFIA, and NUEVA uses 33x more faults than DFIA. Hence, the post-processing technique selected in a biased-fault attack has a significant impact on the probability of a successful attack.

We present eclipse attacks on bitcoin’s peer-to-peer network. Our attack allows an adversary controlling a sufficient number of IP addresses to monopolize all connections to and from a victim bitcoin node. The attacker can then exploit the victim for attacks on bitcoin’s mining and consensus system, including N-confirmation double spending, selfish mining, and adversarial forks in the blockchain. We take a detailed look at bitcoin’s peer-to-peer network, and quantify the resources involved in our attack via probabilistic analysis, Monte Carlo simulations, measurements and experiments with live bitcoin nodes. Finally, we present countermeasures, inspired by botnet architectures, that are designed to raise the bar for eclipse attacks while preserving the openness and decentralization of bitcoin’s current network architecture.

One of the most important benefits of public cloud storage is outsourcing of management and maintenance with easy accessibility and retrievability over the internet. However, outsourcing data on the cloud brings new challenges such as integrity verification and privacy of data. More concretely, once the users outsource their data on the cloud they have no longer physical control over the data and this leads to the integrity protection issue. Hence, it is crucial to guarantee proof of data storage and integrity of the outsourced data. Several pairing-based au- diting solutions have been proposed utilizing the Boneh-Lynn-Shacham (BLS) short signatures. They basically provide a desirable and efficient property of non-repudiation protocols. In this work, we propose the first ID-based privacy-preserving public auditing scheme with message recov- erable signatures. Because of message recoverable auditing scheme, the message itself is implicitly included during the verification step that was not possible in previously proposed auditing schemes. Furthermore, we point out that the algorithm suites of existing schemes is either insecure or very inefficient due to the choice of the underlying bilinear map and its baseline parameter selections. We show that our scheme is more ef- ficient than the recently proposed auditing schemes based on BLS like short signatures.

This paper introduces a new P2P Electronic Cash system called Netcoin. The purpose of Netcoin is to facilitate inexpensive peer-to-peer monetary transactions on the Web. Its salient features are that it is a traceable system with an efficient mechanism for verifying transactions. Netcoins are reusable and can be easily passed from one user to another. The issuing of virtual currency and verification of transactions are performed by trusted mints, which act as the gateway between the fiat and virtual currency worlds. There is no need to maintain a public ledger, which would inhibit use on a global scale because of rapidly increasing memory and bandwidth requirements. The system is neither inflationary nor deflationary in nature and does not purport a new economic model. As a fiat-backed currency it should not suffer the volatility issues associated with Bitcoin. In this paper the two most prominent electronic payment systems of the last forty years, namely Ecash and Bitcoin, are examined. Netcoin is then introduced in detail and is designed to address the shortcomings of these payment systems.

Search engines are the prevalently used tools to collect information about individuals on the Internet. Search results typically comprise a variety of sources that contain personal information --- either intentionally released by the person herself, or unintentionally leaked or published by third parties without being noticed, often with detrimental effects on the individual's privacy. To grant individuals the ability to regain control over their disseminated personal information, the European Court of Justice recently ruled that EU citizens have a right to be forgotten in the sense that indexing systems, such as Google, must offer them technical means to request removal of links from search results that point to sources violating their data protection rights. As of now, these technical means consist of a web form that requires a user to manually identify all relevant links herself upfront and to insert them into the web form, followed by a manual evaluation by employees of the indexing system to assess if the request to remove those links is eligible and lawful. In this work, we propose a universal framework Oblivion to support the automation of the right to be forgotten in a scalable, provable and privacy-preserving manner. First, Oblivion enables a user to automatically find and tag her disseminated personal information using natural language processing (NLP) and image recognition techniques and file a request in a privacy-preserving manner. Second, Oblivion provides indexing systems with an automated and provable eligibility mechanism, asserting that the author of a request is indeed affected by an online resource. The automated eligibility proof ensures censorship-resistance so that only legitimately affected individuals can request the removal of corresponding links from search results. We have conducted comprehensive evaluations of Oblivion, showing that the framework is capable of handling 278 removal requests per second on a standard notebook (2.5 GHz dual core), and is hence suitable for large-scale deployment.

Given the increasing adoption of Bitcoin, the number of transactions and the block sizes within the system are only expected to increase. To sustain its correct operation in spite of its ever-increasing use, Bitcoin implements a number of necessary optimizations and scalability measures. These measures limit the amount of information broadcast in the system to the minimum necessary. In this paper, we show that current scalability measures adopted by Bitcoin come at odds with the security of the system. More specifically, we show that an adversary can exploit these measures in order to effectively delay the propagation of transactions and blocks to specific nodes—without causing a network partitioning in the system. We show that this allows the adversary to easily mount Denial-of-Service attacks, considerably increase its mining advantage in the network, and double-spend transactions in spite of the current countermeasures adopted by Bitcoin. Based on our results, we propose a number of countermeasures in order to enhance the security of Bitcoin without deteriorating its scalability.

Genome sequencing technology has advanced at a rapid pace and it is now possible to generate highly-detailed genotypes inexpensively. The collection and analysis of such data has the potential to support various applications, including personalized medical services. While the benefits of the genomics revolution are trumpeted by the biomedical community, the increased availability of such data has major implications for personal privacy; notably because the genome has certain essential features, which include (but are not limited to) (i) an association with traits and certain diseases, (ii) identification capability (e.g., forensics), and (iii) revelation of family relationships. Moreover, direct-to-consumer DNA testing increases the likelihood that genome data will be made available in less regulated environments, such as the Internet and for-profit companies. The problem of genome data privacy thus resides at the crossroads of computer science, medicine, and public policy. While the computer scientists have addressed data privacy for various data types, there has been less attention dedicated to genomic data. Thus, the goal of this paper is to provide a systematization of knowledge for the computer science community. In doing so, we address some of the (sometimes erroneous) beliefs of this field and we report on a survey we conducted about genome data privacy with biomedical specialists. Then, after characterizing the genome privacy problem, we review the state-of-the-art regarding privacy attacks on genomic data and strategies for mitigating such attacks, as well as contextualizing these attacks from the perspective of medicine and public policy. This paper concludes with an enumeration of the challenges for genome data privacy and presents a framework to systematize the analysis of threats and the design of countermeasures as the field moves forward.

Efficiency is the bottleneck of many cryptographic protocols towards their practical application in different contexts. This holds true also in the context of electronic voting, where cryptographic protocols are used to ensure a diversity of security requirements, e.g. secrecy and integrity of cast votes. A new and promising application area of electronic voting is boardroom voting, which in practice takes place very frequently and often on simple issues such as approving or refusing a budget. Hence, it is not a surprise that a number of cryptographic protocols for boardroom voting have been already proposed. In this work, we introduce a security model adequate for the boardroom voting context. Further, we evaluate the efficiency of four boardroom voting protocols, which to best of our knowledge are the only boardroom voting protocols that satisfy our security model. Finally, we compare the performance of these protocols in different election settings.

In Wireless Sensor Networks(WSNs), a group of users communicating on an unreliable wireless channel can use a group secret. For each session, group manager broadcasts a message containing some keying material, from which only the group members authorized in that session can extract the session key. If a member misses a broadcast message for key, it uses self healing to recover missing session key using most recent broadcast message. However, only self healing does not help if node needs to get most recent session key and have missed the corresponding broadcast. Through mutual healing, a node can request recent broadcast information from a neighboring node and then recover the required key using self-healing. In this paper, we propose a bi-linear pairing based self-healing scheme that reduces communication, storage and computation overhead in comparison to existing bi-linear pairing based self-healing schemes. Then, we discuss the mutual healing scheme that provides mutual authentication and key confirmation without disclosing the node locations to the adversary. The analysis with respect to active adversary shows a significant performance improvement for resource constrained sensor nodes along with the security features such as forward and backward secrecy, resilience against node collusion, node revocation and resistance to impersonation.

Large-scale datasets of consumer behavior might revolutionize the way we gain competitive advantages and increase our knowledge in the respective domains. At the same time, valuable datasets pose potential privacy risks that are difficult to foresee. In this paper we study the impact that the prices from consumers’ purchase histories have on the consumers’ location privacy. We show that using a small set of low-priced product prices from the consumers’ purchase histories, an adversary can determine the country, city, and local retail store where the transaction occurred with high confidence. Our paper demonstrates that even when the product category, precise time of purchase, and currency are removed from the consumers’ purchase history (e.g., for privacy reasons), information about the consumers’ location is leaked. The results are based on three independent datasets containing thousands of low-priced and frequently-bought consumer products. In addition, we show how to identify the local currency, given only the total price of a consumer purchase in a global currency (e.g., in Bitcoin). The results show the existence of location privacy risks when releasing consumer purchase histories. As such, the results highlight the need for systems that hide transaction details in consumer purchase histories.

Smart objects are devices with computational and communication capabilities connected to the Internet forming the so called Internet of Things (IoT). The IoT enables many applications, for instance outdoor lighting control, smart energy and water management, or environmental sensing in a smart city environment. Security in such scenarios remains an open challenge due to the resource-constrained nature of devices and networks or the multiple ways in which opponents can attack the system during the lifecycle of a smart object.This paper firstly reviews security and operational goals in an IoT scenario inspired in a smart city environment. Then, we present a comprehensive and lightweight security architecture to secure the IoT throughout the lifecycle of a device. Our solution relies on the lightweight HIMMO scheme as the building stone and shows how HIMMO is not only efficient resource-wise, but that it enables advanced IoT protocols and deployments. Our design and analysis show that our HIMMO-based security architecture can be easily integrated in existing communication protocols such as IEEE 802.15.4 or OMA LWM2M providing a number of advantages that existing solutions cannot provide both performance and operation-wise.

This work exposes a largely unexplored vector of physical-layer attacks with demonstrated consequences in automobiles. By modifying the physical environment around analog sensors such as Antilock Braking Systems (ABS), we exploit weaknesses in wheel speed sensors so that a malicious attacker can inject arbitrary measurements to the ABS computer which in turn can cause life-threatening situations. In this paper, we describe the development of a prototype ABS spoofer to enable such attacks and the potential consequences of remaining vulnerable to these attacks. The class of sensors sensitive to these attacks depends on the physics of the sensors themselves. ABS relies on magnetic--based wheel speed sensors which are exposed to an external attacker from underneath the body of a vehicle. By placing a thin electromagnetic actuator near the ABS wheel speed sensors, we demonstrate one way in which an attacker can inject magnetic fields to both cancel the true measured signal and inject a malicious signal, thus spoofing the measured wheel speeds. The mounted attack is of a non-invasive nature, requiring no tampering with ABS hardware and making it harder for failure and/or intrusion detection mechanisms to detect the existence of such an attack. This development explores two types of attacks: a disruptive, naive attack aimed to corrupt the measured wheel speed by overwhelming the original signal and a more advanced spoofing attack, designed to inject a counter-signal such that the braking system mistakenly reports a specific velocity. We evaluate the proposed ABS spoofer module using industrial ABS sensors and wheel speed decoders, concluding by outlining the implementation and lifetime considerations of an ABS spoofer with real hardware.

Trying to make it more difficult to hack passwords has a long history. However the research community has not addressed the change of context from traditional Unix mainframe systems to web applications which face new threats (DoS) and have fewer constraints (client-side computation is allowed). In absence of updated guidance, a variety of solutions are scattered all over the web, from amateur to somewhat professional. However, even the best references have issues such as incomplete details, misuse of terminology, assertion of requirements that are not adequately justified, and too many options presented to the developer, opening the door to potential mistakes. The purpose of this research note is to present a solution with complete details and a concise summary of the requirements, and to provide a solution that developers can readily implement with confidence, assuming that the solution is endorsed by the research community. The proposed solution involves client-side processing of a heavy computation in combination with a server-side hash computation. It follows a similar approach to a few other proposals on the web, but is more complete and justified than any that we found.

Cloud brokers have been recently introduced as an additional computational layer to facilitate cloud selection and service management tasks for cloud consumers. However, existing brokerage schemes on cloud service selection typically assume that brokers are completely trusted, and do not provide any guarantee over the correctness of the service recommendations. It is then possible for a compromised or dishonest broker to easily take advantage of the limited capabilities of the clients and provide incorrect or incomplete responses. To address this problem, we propose an innovative Cloud Service Selection Verification (CSSV) scheme and index structures (MMBcloud-tree) to enable cloud clients to detect misbehavior of the cloud brokers during the service selection process. We demonstrate correctness and efficiency of our approaches both theoretically and empirically.

Nowadays, recommender systems have become an indispensable part of our daily life and provide personalized services for almost everything. However, nothing is for free -- such systems have also upset the society with severe privacy concerns because they accumulate a lot of personal information in order to provide recommendations. In this work, we construct privacy-preserving recommendation protocols by incorporating cryptographic techniques and the inherent data characteristics in recommender systems. We first revisit the protocols by Jeckmans et al. at ESORICS 2013 and show a number of security and usability issues. Then, we propose two privacy-preserving protocols, which compute predicted ratings for a user based on inputs from both the user's friends and a set of randomly chosen strangers. A user has the flexibility to retrieve either a predicted rating for an unrated item or the Top-N unrated items. The proposed protocols prevent information leakage from both protocol executions and the protocol outputs: a somewhat homomorphic encryption scheme is used to make all computations run in encrypted form, and inputs from the randomly-chosen strangers guarantee that the inputs of a user's friends will not be compromised even if this user's outputs are leaked. Finally, we use the well-known MovieLens 100k dataset to evaluate the performances for different parameter sizes.

Information leakage is a major concern in modern day IT-security. In fact, a malicious user is often able to extract information about private values from the computation performed on the devices. In specific settings, such as RFID, where a low computational complexity is required, it is hard to apply standard techniques to achieve resilience against this kind of attacks. In this paper, we present a framework to make cryptographic primitives based on large finite fields robust against information leakage with a bounded computational cost. The approach makes use of the inner product extractor and guarantees security in the presence of leakage in a widely accepted model. Furthermore, we show how to apply the proposed techniques to the authentication protocol Lapin, and we compare it to existing solutions.

We show how to provide privacy-preserving (zero-knowledge) answers to order queries on network data that is organized in lists, trees, and partially-ordered sets of bounded dimension. Our methods are efficient and dynamic, in that they allow for updates in the ordering information while also providing for quick and verifiable answers to queries that reveal no information besides the answers to the queries themselves.

We introduce a sorting scheme which is capable of efficiently sorting encrypted data without the secret key. The technique is obtained by focusing on the multiplicative depth of the sorting circuit alongside the more traditional metrics such as number of comparisons and number of iterations. The reduced depth allows much reduced noise growth and thereby makes it possible to select smaller parameter sizes in somewhat homomorphic encryption instantiations resulting in greater efficiency savings. We first consider a number of well known comparison based sorting algorithms as well as some sorting networks, and analyze their circuit implementations with respect to multiplicative depth. In what follows, we introduce a new ranking based sorting scheme and rigorously analyze the multiplicative depth complexity as $O(\log(N)+\log(\ell))$, where $N$ is the size of the array to be sorted and $\ell$ is the bit size of the array elements. Finally, we simulate our sorting scheme using a leveled/batched instantiation of a SWHE library. Our sorting scheme performs favorably over the analyzed classical sorting algorithms.

Bitcoin has emerged as the most successful cryptographic currency in history. Within two years of its quiet launch in 2009, Bitcoin grew to comprise billions of dollars of economic value, even while the body of published research and security analysis justifying the system's design was negligible. In the ensuing years, a growing literature has identified hidden-but-important properties of the system, discovered attacks, proposed promising alternatives, and singled out difficult future challenges. This interest has been complemented by a large and vibrant community of open-source developers who steward the system, while proposing and deploying numerous modifications and extensions. We provide the first systematic exposition of the second generation of cryptocurrencies, including Bitcoin and the many alternatives that have been implemented as alternate protocols or ``altcoins.'' Drawing from a scattered body of knowledge, we put forward three key components of Bitcoin's design that can be decoupled, enabling a more insightful analysis of Bitcoin's properties and its proposed modifications and extensions. We contextualize the literature into five central properties capturing blockchain stability. We map the design space for numerous proposed modification, providing comparative analyses for alternative consensus mechanisms, currency allocation mechanisms, computational puzzles, and key management tools. We focus on anonymity issues in Bitcoin and provide an evaluation framework for analyzing a variety of proposals for enhancing unlinkability. Finally we provide new insights on a what we term disintermediation protocols, which absolve the need for trusted intermediaries in an interesting set of applications. We identify three general disintermediation strategies and provide a detailed comparative cost analysis.

We reinvestigate a notion of {\em one-time programs} introduced in the CRYPTO 2008 paper by Goldwasser {\it et~al.} A one-time program is a device containing a program $C$, with the property that the program $C$ can be executed on at most one input. Goldwasser {\it et~al.}~show how to implement one-time programs on devices equipped with special hardware gadgets called {\em one-time memory} tokens. We provide an alternative construction that does not rely on the hardware gadgets. Instead, it is based on the following assumptions: (1) the total amount of data that can leak from the device is bounded, and (2) the total memory on the device (available both to the honest user and to the attacker) is also restricted, which is essentially the model used recently by Dziembowski {\it et al.}\ (TCC 2011, CRYPTO 2011) to construct one-time computable {\em pseudorandom} functions and key-evolution schemes.

This new protocol is based on the idea of introducing a revocable anonymity in Tor, which was presented in our recent paper entitled "Another Tor is possible". Compared to that previous paper, this present scheme simplify the first protocol and reduce the power of the directory server, while maintaining the ability for the Tor community, to break the anonymity of a sender in case of misconduct. We also take the opportunity of this paper, to appeal the majors internet companies, to help in the creation of a responsible Tor network (without pedophiles, spies, ....), by mixing billions of data flowing through their networks with those of Tor.

A rapid growth of Machine-to-Machine (M2M) communications is expected in the coming years. M2M applications create new challenges for in-field testing since they typically operate in environments where human supervision is difficult or impossible. In addition, M2M networks may be significant in size. We propose to automate Logic Built-In Self-Test (LBIST) by using a centralized test management system which can test all end-point M2M devices in the same network. Such a method makes possible transferring some of the LBIST functionality from the devices under test to the test management system. This is important for M2M devices which have very limited computing resources and commonly are battery-powered. In addition, the presented method provides protection against both random and malicious faults including some types of hardware Trojans.

We introduce quantitative usability and security models to guide the design of \emph{password management schemes} --- systematic strategies to help users create and remember multiple passwords. In the same way that security proofs in cryptography are based on complexity-theoretic assumptions (e.g., hardness of factoring and discrete logarithm), we quantify usability by introducing \emph{usability assumptions}. In particular, password management relies on assumptions about human memory, e.g., that a user who follows a particular rehearsal schedule will successfully maintain the corresponding memory. These assumptions are informed by research in cognitive science and can be tested empirically. Given rehearsal requirements and a user's visitation schedule for each account, we use the total number of extra rehearsals that the user would have to do to remember all of his passwords as a measure of the usability of the password scheme. Our usability model leads us to a key observation: password reuse benefits users not only by reducing the number of passwords that the user has to memorize, but more importantly by increasing the natural rehearsal rate for each password. We also present a security model which accounts for the complexity of password management with multiple accounts and associated threats, including online, offline, and plaintext password leak attacks. Observing that current password management schemes are either insecure or unusable, we present Shared Cues--- a new scheme in which the underlying secret is strategically shared across accounts to ensure that most rehearsal requirements are satisfied naturally while simultaneously providing strong security. The construction uses the Chinese Remainder Theorem to achieve these competing goals.

Ring signature enables an user to anonymously sign a message on behalf of a group of users termed as ‘ring’ formed in an ‘ad-hoc’ manner. A naive scheme produces a signature linear in the size of the ring, but this is extremely inefficient when ring size is large. Dodis et al. proposed a constant size scheme in EUROCRYPT’13, but provably secure in random oracle model. Best known result without random oracle is a sub-linear size construction by Chandran et al. in ICALP’07 and a follow-up work by Essam Ghadafi in IMACC’13. Therefore, construction of a constant size ring signature scheme without random oracle meeting stringent security requirement still remains as an interesting open problem. Our first contribution is a generic technique to convert a compatible signature scheme to a constantsized ring signature scheme. The technique employs a constant size set membership check that may be of independent interest. Our construction is instantiated over asymmetric pairing of composite order and optimally efficient. The scheme meets strongest security requirements, viz. anonymity under full key exposure and unforgeability against insider-corruption without using random oracle under simple hardness assumptions. We also provide a concrete instantiation of the scheme based on Full Boneh-Boyen signatures.

We present a side-channel attack based on remanence decay in volatile memory and show how it can be exploited effectively to launch a non-invasive cloning attack against SRAM PUFs --- an important class of PUFs typically proposed as lightweight security primitive with low overhead by using the existing memory of the underlying device. We validate our approach against two SRAM PUF implementations in 65~nm CMOS ASICs. We discuss countermeasures against our attack and propose the constructive use of remanence decay to improve the cloning-resistance of SRAM PUFs. Moreover, as a further contribution of independent interest, we show how to use our evaluation results to significantly improve the performance of the recently proposed TARDIS scheme, which is based on remanence decay in SRAM and used as a time-keeping mechanism for low-power clock-less devices.

A number of databases around the world currently host a wealth of genomic data that is invaluable to researchers conducting a variety of genomic studies. However, patients who volunteer their genomic data run the risk of privacy invasion. In this work, we give a cryptographic solution to this problem: to maintain patient privacy, we propose encrypting all genomic data in the database. To allow meaningful computation on the encrypted data, we propose using a homomorphic encryption scheme. Specifically, we take basic genomic algorithms which are commonly used in genetic association studies and show how they can be made to work on encrypted genotype and phenotype data. In particular, we consider the Pearson Goodness-of-Fit test, the D' and r^2-measures of linkage disequilibrium, the Estimation Maximization (EM) algorithm for haplotyping, and the Cochran-Armitage Test for Trend. We also provide performance numbers for running these algorithms on encrypted data.

CryptDB has been proposed as a practical and secure middleware to protect databases deployed on semi-honest cloud servers. While CryptDB provides sufficient protection under Threat-1, here we demonstrate that when CryptDB is deployed to secure the cloud hosted database of a realistic web application, an attacker to database or a Malicious Database Administrator (mDBA) can easily steal information, and even escalate his privilege to become the administrator of the web application. Our attacks, fall under a restricted form of Threat-2 where we only assume that the attackers or the mDBA tampers with the CryptDB protected database and is opens an ordinary user account through the web application. Our attacks, are carried out assuming perfectly secure proxy and application servers. Therefore, the attacks work without recovering the master key residing on the proxy server. At the root of the attack lies the lack of any integrity checks for the data in the CryptDB database. We propose a number of practical countermeasures to mitigate attacks targeting the integrity of the CryptDB database. We also demonstrate that the data integrity is not sufficient to protect the databases, when query integrity and frequency attacks are considered.

In this paper it is shown that the use of Jordan normal form instead of Hermite normal form would improve substantially the efficiency and the security of the lattice based signature scheme. In this scheme we also use a new hash function in such a way that the efficiency improved is obtain without decreasing the security of the function.

PKCS\#11 is a very popular cryptographic API: it is the standard used by many Hardware Security Modules, smartcards and software cryptographic tokens. Several attacks have been uncovered against PKCS\#11 at different levels: intrinsic logical flaws, cryptographic vulnerabilities or severe compliance issues. Since affected hardware remains widespread in computer infrastructures, we propose a user-centric and pragmatic approach for secure usage of vulnerable devices. We introduce \textit{Caml Crush}, a PKCS\#11 filtering proxy. Our solution allows to dynamically protect PKCS\#11 cryptographic tokens from state of the art attacks. This is the first approach that is immediately applicable to commercially available products. We provide a fully functional open source implementation with an extensible filter engine effectively shielding critical resources. This yields additional advantages to using \textit{Caml Crush} that go beyond classical PKCS\#11 weakness mitigations.

Side-channel attacks using only a single trace crucially rely on the capability of reliably extracting side-channel information (e.g. Hamming weights of intermediate target values) from traces. In particular, in original versions of simple power analysis (SPA) or algebraic side channel attacks (ASCA) it was assumed that an adversary can correctly extract the Hamming weight values for all the intermediates used in an attack. Recent developments in error tolerant SPA style attacks relax this unrealistic requirement on the information extraction and bring renewed interest to the topic of template building or training suitable machine learning classifiers. In this work we ask which classifiers or methods, if any, are most likely to return the true Hamming weight among their first (say $s$) ranked outputs. We experiment on two data sets with different leakage characteristics. Our experiments show that the most suitable classifiers to reach the required performance for pragmatic SPA attacks are Gaussian templates, Support Vector Machines and Random Forests, across the two data sets that we considered. We found no configuration that was able to satisfy the requirements of an error tolerant ASCA in case of complex leakage.

We find mathematically optimal side-channel distinguishers by looking at the side-channel as a communication channel. Our methodology can be adapted to any given scenario (device, signal-to-noise ratio, noise distribution, leakage model, etc.). When the model is known and the noise is Gaussian, the optimal distinguisher outperforms CPA and covariance. However, we show that CPA is optimal when the model is only known on a proportional scale. For non-Gaussian noise, we obtain different optimal distinguishers, one for each noise distribution. When the model is imperfectly known, we consider the scenario of a weighted sum of the sensitive variable bits where the weights are unknown and drawn from a normal law. In this case, our optimal distinguisher performs better than the classical linear regression analysis.

A pure peer to peer version of the exchange system would allow all parties access to the market without relying on any central organization for market access. Paper proposes a solution for the problem of maintain an order book and determine the execution rate in the peer to peer network. Like crypto-currencies the network relies on blockchain of transaction. Digital signature system would be the core of the decentralized market place. The paper defines basic ground rules for the working of decentralized exchange. The major components of the decentralized exchange are issuing process, co-existence of blockchain and order books and functions of the miner. Unlike other crypto currencies de-centralized exchange would have a trust based issuing process which in long run would be a sum zero game. The decentralized Exchange would have 3 types of entities namely – Issuer, Trader and Miner.

With the rise of Internet computing, outsourcing difficult computational tasks became an important need. Yet, once the computation is outsourced, the job owner loses control, and hence it is crucial to provide guarantees against malicious actions of the contractors involved. Cryptographers have an almost perfect solution, called fully homomorphic encryption, to this problem. This solution hides both the job itself and any inputs to it from the contractors, while still enabling them to perform the necessary computation over the encrypted data. This is a very strong security guarantee, but the current constructions are highly impractical. In this paper, we propose a different approach to outsourcing computational tasks. We are not concerned with hiding the job or the data, but our main task is to ensure that the job is computed correctly. We also observe that not all contractors are malicious; rather, majority are rational. Thus, our approach brings together elements from cryptography, as well as game theory and mechanism design. We achieve the following results: (1) We incentivize all the rational contractors to perform the outsourced job correctly, (2) we guarantee high fraction (e.g., 99.9%) of correct results even in the existence of a relatively large fraction (e.g., 33%) of malicious irrational contractors in the system, (3) and we show that our system achieves these while being almost as efficient as running the job locally (e.g., with only 3% overhead). Such a high correctness guarantee was not known to be achieved with such efficiency.

Cloud computing sparked interest in Verifiable Computation protocols, which allow a weak client to securely outsource computations to remote parties. Recent work has dramatically reduced the client’s cost to verify the correctness of results, but the overhead to produce proofs largely remains impractical. Geppetto introduces complementary techniques for reducing prover overhead and increasing prover flexibility. With Multi-QAPs, Geppetto reduces the cost of sharing state between computations (e.g., for MapReduce) or within a single computation by up to two orders of magnitude. Via a careful instantiation of cryptographic primitives, Geppetto also brings down the cost of verifying outsourced cryptographic computations (e.g., verifiably computing on signed data); together with Geppetto’s notion of bounded proof bootstrapping, Geppetto improves on prior bootstrapped systems by five orders of magnitude, albeit at some cost in universality. Geppetto also supports qualitatively new properties like verifying the correct execution of proprietary (i.e., secret) algorithms. Finally, Geppetto’s use of energy-saving circuits brings the prover’s costs more in line with the program’s actual (rather than worst-case) execution time. Geppetto is implemented in a full-fledged, scalable compiler that consumes LLVM code generated from a variety of apps, as well as a large cryptographic library.

Face recognition is one of the most important biometrics pattern recognitions, which has been widely applied in a variety of enterprise, civilian and law enforcement. The privacy of biometrics data raises important concerns, in particular if computations over biometric data is performed at untrusted servers. In previous work of privacy-preserving face recognition, in order to protect individuals' privacy, face recognition is performed over encrypted face images. However, these results increase the computation cost of the client and the face database owners, which may enable face recognition cannot be efficiently executed. Consequently, it would be desirable to reduce computation over sensitive biometric data in such environments. Currently, no secure techniques for outsourcing face biometric recognition is readily available. In this paper, we propose a privacy-preserving face recognition protocol with outsourced computation for the first time, which efficiently protects individuals' privacy. Our protocol substantially improves the previous works in terms of the online computation cost by outsourcing large computation task to a cloud server who has large computing power. In particular, the overall online computation cost of the client and the database owner in our protocol is at most 1/2 of the corresponding protocol in the state of the art algorithms. In addition, the client requires the decryption operations with only $O(1)$ independent of $M$, where $M$ is the size of the face database. Furthermore, the client can verify the correction of the recognition result.

The Blind Seer system (Oakland 2014) is an efficient and scalable DBMS that affords both client query privacy and server data protection. It also provides the ability to enforce authorization policies on the system, restricting client’s queries while maintaining the privacy of both query and policy. Blind Seer supports a rich query set, including arbitrary boolean formulas, and is provably secure with respect to a controlled amount of search pattern leakage. No other system to date achieves this tradeoff of performance, generality, and provable privacy. A major shortcoming of Blind Seer is its reliance on semi-honest security, particularly for access control and data protection. A malicious client could easily cheat the query authorization policy and obtain any database records satisfying any query of its choice, thus violating basic security features of any standard DBMS. In sum, Blind Seer offers additional privacy to a client, but sacrifices a basic security tenet of DBMS. In the present work, we completely resolve the issue of a malicious client. We show how to achieve robust access control and data protection in Blind Seer with virtually no added cost to performance or privacy. Our approach also involves a novel technique for a semi-private function secure function evaluation (SPF-SFE) that may have independent applications. We fully implement our solution and report on its performance.

A protection circuit can be added into cryptographic systems to detect both soft errors and injected faults required by Differential Fault Analysis (DFA) attacks. While such protection can improve the reliability of the target devices significantly and counteract DFA, they will also incur extra power consumption and other resource overhead. In this paper, we analyze the side-channel power leakage of AES protection methods against fault attacks and quantify the amount. We implement six different schemes and launch correlation power analysis attacks on them. The results show that the protection circuits have all increased the power leakage and therefore make the system more vulnerable to power analysis attacks. We further compare different protection schemes in terms of power consumption, area, fault coverage, and side-channel leakage. Our results demonstrate trade-offs among multiple design metrics, and suggest that reliability, security, and costs have to be all considered together in the design phase of cryptographic systems.

Abstract—Voting systems based on paper ballots has a long history with various problems. Vote-selling and correct outcome are two major problems among many. In this work, we propose a new solution to these problems by using UltraViolet (UV) fiber paper Physical Unclonable Function (PUF). When applied this solution not only prevents vote-selling but also ensures the correctness of the outcome. With these two problems eliminated, the voting systems based on paper ballots will have complete integrity.

Lightweight Bitcoin clients are gaining increasing adoption among Bitcoin users, owing to their reduced resource and bandwidth consumption. These clients support a simplified payment verification (SPV) mode as they are only required to download and verify a part of the block chain — thus supporting the usage of Bitcoin on constrained devices, such as smartphones. SPV clients rely on Bloom filters to receive transactions that are relevant to their local wallet. These filters embed all the Bitcoin addresses used by the SPV clients, and are outsourced to more powerful Bitcoin nodes which then only forward to those clients transactions relevant to their outsourced Bloom filters. In this paper, we explore the privacy of existing SPV clients. We show analytically and empirically that the reliance on Bloom filters within existing SPV clients leaks considerable information about the addresses of Bitcoin users. Our results show that an SPV client who uses a modest number of Bitcoin addresses (e.g., < 20) risks revealing almost all of his addresses. We also show that this information leakage is further exacerbated when users restart their SPV clients and/or when the adversary has access to more than one Bloom filter pertaining to the same SPV client. Motivated by these findings, we propose an efficient countermeasure to enhance the privacy of users which rely on SPV clients; our proposal can be directly integrated within existing SPV client implementations.

Private query processing on encrypted databases allows users to obtain data from encrypted databases in such a way that the user's sensitive data will be protected from exposure. Given an encrypted database, the users typically submit queries similar to the following examples: - How many employees in an organization make over 100,000? - What is the average age of factory workers suffering from leukemia? Answering the above questions requires one to \textbf{search} and then \textbf{compute} over the encrypted databases \emph{in sequence}. In the case of privately processing queries with only one of these operations, many efficient solutions have been developed using a special-purpose encryption scheme (e.g., searchable encryption). In this paper, we are interested in efficiently processing queries that need to perform both operations on \emph{fully} encrypted databases. One immediate solution is to use several special-purpose encryption schemes at the same time, but this approach is associated with a high computational cost for maintaining multiple encryption contexts. The other solution is to use a privacy homomorphism (or fully homomorphic encryption) scheme. However, no secure solutions have been developed that meet the efficiency requirements. In this work, we construct a unified framework so as to efficiently and privately process queries with ``search'' and ``compute'' operations. To this end, the first part of our work involves devising some underlying circuits as primitives for queries on encrypted data. Second, we apply two optimization techniques to improve the efficiency of the circuit primitives. One technique is to exploit SIMD techniques to accelerate their basic operations. In contrast to general SIMD approaches, our SIMD implementation can be applied even when one basic operation is executed. The other technique is to take a large integer ring (\textit{e.g.}, $\Z_{2^{t}}$) as a message space instead of a binary field. Even for an integer of $k$ bits with $k>t$, addition can be performed with degree 1 circuits with lazy carry operations. As a result, search queries including a conjunctive or disjunctive query on encrypted databases of $N$ tuples with $\mu$-bit attributes require $\bigo(N \log \mu)$ homomorphic operations with depth $\bigo(\log \mu)$ circuits. Search-and-compute queries, such as a conjunctive query with aggregate functions in the same conditions, are processed using $\bigo(\mu N)$ homomorphic operations with at most depth $\bigo(\log \mu \log N)$ circuits. Further, we can process search-and-compute queries using only $\bigo(N \log \mu)$ homomorphic operations with depth $\bigo(\log \mu)$ circuits, even in the large domain. Finally, we present various experiments by varying the parameters, such as the query type and the number of tuples.

The aim of this paper is to introduce some modifications in Tor, in order to improve user’s anonymity and relay’s security. Thus, we introduced a system that will ensure anonymity for all users, while maintaining the ability to break the anonymity of a sender in case of misconduct. The revocation of the anonymity will require the use of secret sharing schemes, since we assume that, the lifting of the anonymity of the dishonest user should not depend on a single entity, but on a consensus within the network. In addition to the revocation of the anonymity, we propose in this paper further improvements such as mixing Tor traffic with those of the major internet groups, using the camouflage, or introducing a honeypot in the network.

Security is the biggest concern in Wireless Sensor Networks (WSNs) especially for the ones which are deployed for military applications and monitoring. They are prone to various attacks which degrades the network performance very rapidly. Sometimes multiple attacks are launched in the network using hybrid anomaly. In this situation it is very difficult to find out which kind of anomaly is activated. In this paper, we have proposed a hybrid anomaly detection technique with the application of k-means clustering. The analysis of the network data set consists of traffic data and end to end delay data is performed. The data set is clustered using weka 3.6.10. After clustering, we get the threshold values of various network performance parameters (traffic and delay). These threshold values are used by the hybrid anomaly detection technique to detect the anomaly. During the experimentation, it has been observed that two types of anomalies are activated in the network causing misdirection and blackhole attacks.

Participatory sensing enables new paradigms and markets for information collection based on the ubiquitous availability of smartphones, but also introduces privacy challenges for participating users and their data. In this work, we review existing security models for privacy-preserving participatory sensing and propose several improvements that are both of theoretical and practical significance. We first address an important drawback of prior work, namely the lack of consideration of collusion attacks that are highly relevant for such multi-user settings. We explain why existing security models are insufficient and why previous protocols become insecure in the presence of colluding parties. We remedy this problem by providing new security and privacy definitions that guarantee meaningful forms of collusion resistance. We propose new collusion-resistant participatory sensing protocols satisfying our definitions: a generic construction that uses anonymous identity-based encryption (IBE) and its practical instantiation based on the Boneh-Franklin IBE scheme. We then extend the functionality of participatory sensing by adding the ability to perform aggregation on the data submitted by the users, without sacrificing their privacy. We realize this through an additively-homomorphic IBE scheme which in turn is constructed by slightly modifying the Boneh-Franklin IBE scheme. From a practical point of view, the resulting scheme is suitable for calculations with small sensor readings/values such as temperature measurements, noise levels, or prices, which is sufficient for many applications of participatory sensing.

With sensitive data being increasingly stored on mobile devices and laptops, hard disk encryption is more important than ever. In particular, being able to plausibly deny that a hard disk contains certain information is a very useful and interesting research goal. However, it has been known for some time that existing ``hidden volume'' solutions, like TrueCrypt, fail in the face of an adversary who is able to observe the contents of a disk on multiple, separate occasions. In this work, we explore more robust constructions for hidden volumes and present HIVE, which is resistant to more powerful adversaries with multiple-snapshot capabilities. In pursuit of this, we propose the first security definitions for hidden volumes, and prove HIVE secure under these definitions. At the core of HIVE, we design a new write-only Oblivious RAM. We show that, when only hiding writes, it is possible to achieve ORAM with optimal O(1) communication complexity and only poly-logarithmic user memory. This is a significant improvement over existing work and an independently interesting result. We go on to show that our write-only ORAM is specially equipped to provide hidden volume functionality with low overhead and significantly increased security. Finally, we implement HIVE as a Linux kernel block device to show both its practicality and usefulness on existing platforms.

We present security proofs for the BLT signature scheme in the model, where hash functions are built from ideal components (random oracles, ideal ciphers, etc.). We show that certain strengthening of the Pre-image Awareness (PrA) conditions like boundedness of the extractor, and certain natural properties (balancedness and the so-called output one-wayness) of the hash function are sufficient for existential unforgeability of the BLT signature scheme.

The technological advance is entering almost all aspects of our everyday life. One interesting aspect is the possibility to conduct elections over the Internet. However, many proposed Internet voting schemes and systems build on unrealistic assumptions about the trustworthiness of the voting environment and other voter-side assumptions. Code voting -- first introduced by Chaum [Cha01] -- is one approach that minimizes the voter-side assumptions. The voting scheme Pretty UnderstandableDemocracy [BNOV13] builds on the idea of code voting while it ensures on the server-side an arguably practical security model based on a strict separation of duty, i.e. all security requirements are ensured if any two components do not collaborate in order to violate the corresponding requirement. As code voting and strict separation of duty realizations come along with some challenges (e.g. pre-auditing phase, usability issues, clearAPIs), the goal of our research was to implement Pretty UnderstandableDemocracy and run a trial election. This paper reports about necessary refinements of the original scheme, the implementation process, and atrial election among the different development teams (each team being responsible for one component).

Computing aggregate statistics about user data is of vital importance for a variety of services and systems, but this practice has been shown to seriously undermine the privacy of users. Differential privacy has proved to be an effective tool to sanitize queries over a database, and various cryptographic protocols have been recently proposed to enforce differential privacy in a distributed setting, e.g., statical queries on sensitive data stored on the user’s side. The widespread deployment of differential privacy techniques in real-life settings is, however, undermined by several limitations that existing constructions suffer from: they support only a limited class of queries, they pose a trade-off between privacy and utility of the query result, they are affected by the answer pollution problem, or they are inefficient. This paper presents PrivaDA, a novel design architecture for distributed differential privacy that leverages recent advances in SMPCs on fixed and floating point arithmetics to overcome the previously mentioned limitations. In particular, PrivaDA supports a variety of perturbation mechanisms (e.g., the Laplace, discrete Laplace, and exponential mechanisms) and it constitutes the first generic technique to generate noise in a fully distributed manner while maintaining the optimal utility. Furthermore, PrivaDA does not suffer from the answer pollution problem. We demonstrate the efficiency of PrivaDA with a performance evaluation, and its expressiveness and flexibility by illustrating a variety of application scenarios such as privacy-preserving web analytics.

In order to satisfy the different requirements of provable data possession in cloud computing, a multi-function provable data possession (MF-PDP) is proposed, which supports public verification, data dynamic, unlimited times verification, sampling verification. Besides, it is security in RO model and it is verification privacy under half trust model and can prevent from replacing attack and replay attack. The detail design is provided and the theory analysis about the correct, security and performance are also described. The experiment emulation and compare analysis suggest the feasibility and advantage.

Structure-preserving signature schemes can be very useful in the construction of new cryptographic operations like blind signatures. Recently several of these schemes have been proposed. The security of signature-preserving signature schemes is still proved by hand, which can be a laborious task. One of the ways to prove security of these schemes algebraic analysis can be used. We present an approach to perform this analysis and the first tool, CheckSPS, that can do an algebraic security analysis of these schemes, using SMT solvers as backend. This can help in constructing new schemes and analyse existing schemes. Our tool can handle all the common security objectives for signature schemes, i.e. existential unforgeability and strong existential unforgeability, and all the common capabilities for adversaries, i.e. random message attacks, non-adaptive chosen message attacks and adaptive chosen message attacks. The tool is sound, so if an attack is found it is actually possible to construct a forged signature.

We propose a log signing scheme that enables (a) verification of the integrity of the whole log, and (b) presentation of any record, along with a compact proof that the record has not been altered since the log was signed, without leaking any information about the contents of other records in the log. We give a formal proof of the security of the proposed scheme, discuss practical considerations, and provide an implementation case study.

Over the past few years, online service providers have started gathering increasing amounts of personal information to build user profiles and monetize them with advertisers and data brokers. Users have little control of what information is processed and are often left with an all-or-nothing decision between receiving free services or refusing to be profiled. This paper explores an alternative approach where users only disclose an aggregate model -- the ``gist'' -- of their data. We aim to preserve data utility and simultaneously provide user privacy. We show that this approach can be efficiently supported by letting users contribute encrypted and differentially-private data to an aggregator. The aggregator combines encrypted contributions and can only extract an aggregate model of the underlying data. We evaluate our framework on a dataset of 100,000 U.S. users obtained from the U.S. Census Bureau and show that (i) it provides accurate aggregates with as little as 100 users, (ii) it generates revenue for both users and data brokers, and (iii) its overhead is appreciably low.

Route Origin Verification (ROVER), a mechanism for securing interdomain routing with BGP, is a proposed alternative to the Resource Public Key Infrastructure (RPKI). While the RPKI requires the design and deployment of a completely new security infrastructure, ROVER leverages existing reverse DNS and DNSSEC deployments. Both ROVER and RPKI are based on a hierarchy of authorities that are trusted to provide information about the routing system. It has been argued recently that misconfigurations or compromises of the RPKI's trusted authorities can present new risks to the routing system. Meanwhile, the advocates of ROVER claim that it provides a "fail-safe" approach, where the Internet will continue to work as it is even when ROVER fails. This poster therefore compares the impact of ROVER failures to those of the RPKI.

In this paper, we study of the notion of differing-input obfuscation, introduced by Barak et al. (CRYPTO 2001, JACM 2012). For any two circuits C_0 and C_1, a differing-input obfuscator diO guarantees that the non-existence of an adversary that can find an input on which C_0 and C_1 differ implies that diO(C_0) and diO(C_1) are computationally indistinguishable. We show many applications of this notion: - We define the notion of a differing-input obfuscator for Turing machines and give a construction for the same (without converting it to a circuit) with input-specific running times. More specifically, for each input, our obfuscated Turning machine takes time proportional to the running time of the Turing machine on that specific input rather than the machine's worst-case running time. - We give a functional encryption scheme that allows for secret-keys to be associated with Turing machines, and thereby achieves input-specific running times. Further, we can equip our functional encryption scheme with delegation properties. - We construct a multi-party non-interactive key exchange protocol with no trusted setup where all parties post only logarithmic-size messages. It is the first such scheme with such short messages. We similarly obtain a broadcast encryption system where the ciphertext overhead and secret-key size is constant (i.e. independent of the number of users), and the public key is logarithmic in the number of users. All our constructions make inherent use of the power provided by differing-input obfuscation. It is not currently known how to construct systems with these properties from the weaker notion of indistinguishability obfuscation.

The modification of message that meets the sufficient conditions for collision is found in the last step of differential attack proposed by Wang et all. (2005) on MD4 hash algorithm. Here we show how this attack phase, finding a collision starting from the list of sufficient conditions for the collision, can be implemented using a combination of two algorithms - evolutionary algorithm and hill climbing. Hybridization of evolutionary algorithm and hill climbing is a well-known technique for improving solutions, but it isn't applied to this domain (at least by information that author has collected).

While expensive cryptographically verifiable computation aims at defeating malicious agents, many civil purposes of outsourced computation tolerate a weaker notion of security, i.e., ``lazy-but-honest'' contractors. Targeting this type of agents, we develop optimal contracts for outsourcing of computational tasks via appropriate use of rewards, punishments, auditing rate, and ``redundancy''. Our contracts provably minimize the expense of the outsourcer (principal) while guaranteeing correct computation. Furthermore, we incorporate practical restrictions of the maximum enforceable fine, limited and/or costly auditing, and bounded budget of the outsourcer. By examining the optimal contracts, we provide insights on how resources should be utilized when auditing capacity and enforceability are limited. Finally, we present a light-weight cryptographic implementation of the contracts and discuss a comparison across different implementations of auditing in outsourced computation.

We propose a simple cast-as-intended remote e-voting protocol where the security is based on the use of secure (and trusted) smart cards that incorporate incard numeric keyboards and LCD displays, and can perform a limited number of cryptographic operations (like encryption, signing, and random number generation). The protocol, while very simple, is significantly more secure (in the sense of ``cast-as-intended'') and convenient to use than the e-voting protocol currently used in Norway. The protocol is developed primarily with the idea of deploying it in Estonia within the next $3$ to $10$ years. Since in Estonia, a vast majority of the population already has ID-cards with digital signing and authentication functionality, and the use of ID-cards is a required prerequisite to participate in Estonian e-voting anyway, our assumption of every voter having a secure hardware token makes sense in this concrete context.

Enabling private database queries is an important and challenging research problem with many real-world applications. The goal is for the client to obtain the results of its queries without learning anything else about the database, while the outsourced server learns nothing about the queries or data, including access patterns. The secure-computation-over-ORAM architecture offers a promising approach to this problem, permitting sub-linear time processing of the queries (after pre-processing) without compromising security. In this work we examine the feasibility of this approach, focusing specifically on secure-computation protocols based on somewhat-homomorphic encryption (SWHE). We devised and implemented secure two-party protocols in the semi-honest model for the path-ORAM protocol of Stefanov et al. This provides access by index or keyword, which we extend (via pre-processing) to limited conjunction queries and range queries. Some of our sub-protocols may be interesting in their own right, such as our new protocols for encrypted comparisons and blinded permutations. We implemented our protocols on top of the HElib homomorphic encryption library. Our basic single-threaded implementation takes about 30 minutes to process a query on a database with $2^{22}$ records and 120-bit long keywords, providing a cause for optimism about the viability of this direction, and we expect a better optimized implementation to be much faster.

Increasingly, confidential medical records are being stored in data centers hosted by hospitals or large companies. As sophisticated algorithms for predictive analysis on medical data continue to be developed, it is likely that, in the future, more and more computation will be done on private patient data. While encryption provides a tool for assuring the privacy of medical information, it limits the functionality for operating on such data. Conventional encryption methods used today provide only very restricted possibilities or none at all to operate on encrypted data without decrypting it first. Homomorphic encryption provides a tool for handling such computations on encrypted data, without decrypting the data, and without even needing the decryption key. In this paper, we discuss possible application scenarios for homomorphic encryption in order to ensure privacy of sensitive medical data. We describe how to privately conduct predictive analysis tasks on encrypted data using homomorphic encryption. As a proof of concept, we present a working implementation of a prediction service running in the cloud (hosted on Microsoft's Windows Azure), which takes as input private encrypted health data, and returns the probability of suffering cardiovascular disease in encrypted form. Since the cloud service uses homomorphic encryption, it makes this prediction while handling only encrypted data, learning nothing about the submitted confidential medical data.

Recently, Juels and Rivest proposed honeywords (decoy pass- words) to detect attacks against hashed password databases. For each user account, the legitimate password is stored with several honeywords in order to sense impersonation. If honeywords are selected properly, an adversary who steals a file of hashed passwords cannot be sure if it is the real password or a honeyword for any account. Moreover, entering with a honeyword to login will trigger an alarm notifying the administrator about a password file breach. At the expense of increasing storage requirement by 20 times, the authors introduce a simple and effective solution to detection of password file disclosure events. In this study, we scrutinize the honeyword system and present some remarks to highlight possible weak points. Also, we suggest an alternative approach that selects honeywords from existing user passwords in the system to provide realistic honeywords – a perfectly flat honeyword generation method – and also to reduce storage cost of the honeyword scheme.

M3lcrypt (canonical M3lcryptH) is a password based key derivation function built around the Merkle-Damgard hash function H. It supports large [pseudo]random salt values (>= 128-bit) and password lengths.

We propose Mixcoin, a protocol to facilitate anonymous payments in Bitcoin and similar cryptocurrencies. We build on the emergent phenomenon of currency mixes, adding an accountability mechanism to expose theft. We demonstrate that incentives of mixes and clients can be aligned to ensure that rational mixes will not steal. Our scheme is efficient and fully compatible with Bitcoin. Against a passive attacker, our scheme provides an anonymity set of all other users mixing coins contemporaneously. This is an interesting new property with no clear analog in better-studied communication mixes. Against active attackers our scheme offers similar anonymity to traditional communication mixes.

We propose a flexible, fairly general, coding for tree hash modes. The coding does not define a tree hash mode, but instead specifies a way to format the message blocks and chaining values into inputs to the underlying function for any topology, including sequential hashing. The main benefit is to avoid input clashes between different tree growing strategies, even before the hashing modes are defined, and to make the SHA-3 standard tree-hashing ready.

The sweeping success of the original (2008) bitcoin protocol proves that digital currency has arrived. The mounting opposition from the financial establishment indicates an overshoot. We propose to tame bitcoin into bitcoin.BitMint: keeping the bitcoin excitement -- fitted into real world security, stability and fraud concerns. The basic idea is to excise the bitcoin money generation formula, and otherwise apply bitcoin essentially “as is” over digital coins which are redeemable by the mint that minted them. This will preserve the bitcoin assured anonymity. The new bitcoin.BitMint solution will benefit from bitcoin’s double-spending prevention, and would otherwise enjoy all the benefits associated with money in a digital form. bitcoin.BitMint will allow traders to invest in US$, gold, or any other commodity while practicing their trade in cyberspace, anonymously, securely, and non-speculatively. This “mint-in-the-middle” protocol will allow law enforcement authorities to execute a proper court order to enforce the disclosure of a suspected fraudster, but the community of honest traders will trade with robust privacy as offered by the original bitcoin protocol. We envision interlinked bitcoin.BitMint trading environments, integrated via an InterMint protocol: a framework for the evolution of a cascaded super currency – global and highly stable.

Bitcoin is a peer-to-peer (p2p) electronic cash system that uses a distributed timestamp service to record transactions in a public ledger (called the Blockchain). A critical component of Bitcoin’s success is the decentralized nature of its architecture, which does not require or even support the establishment of trusted authorities. Yet the absence of certification creates obstacles to its wider acceptance in e-commerce and official uses. We propose a certification system for Bitcoin that offers: a) an opt-in guarantee to send and receive bitcoins only to/ from certified users; b) control of creation of bitcoins addresses (certified users) by trusted authorities. Our proposal may encourage the adoption of Bitcoin in different scenarios that require an officially recognized currency, such as tax payments—often an integral part of e-commerce transactions.

Sealed-Bid auction is an efficient and rational method to establish the price in open market. However sealed-bid auctions are sub- ject to bid-rigging attack. Receipt-free mechanisms were proposed to prevent bid-rigging. The prior receipt-free mechanisms are based on two assumptions; firstly, existence of untappable channel between bidders and auction authorities. Secondly, mechanisms assume the authorities to be honest (not colluding). Moreover the bandwidth required to com- municate the receipt-free bids is huge. This paper presents a sealed-bid auction mechanism to resist bid-rigging. The proposed method does not assume untappable channel nor consider the authorities to be necessarily honest. The proposed mechanism also manages the bandwidth efficiently, and improves the performance of the system.

Instant messaging services are quickly becoming the most dominant form of communication among consumers around the world. Apple iMessage, for example, handles over 2 billion message each day, while WhatsApp claims 16 billion messages from 400 million international users. To protect user privacy, these services typically implement end-to-end and transport layer encryption, which are meant to make eavesdropping infeasible even for the service providers themselves. In this paper, however, we show that it is possible for an eavesdropper to learn information about user actions, the language of messages, and even the length of those messages with greater than 96% accuracy despite the use of state-of-the-art encryption technologies simply by observing the sizes of encrypted packet. While our evaluation focuses on Apple iMessage, the attacks are completely generic and we show how they can be applied to many popular messaging services, including WhatsApp, Viber, and Telegram.

Coherent light, as produced by lasers, gives rise to an intrinsic noise, known as quantum noise, optical noise or shot noise. AlphaEta is a protocol which exploits this physical phenomenon to obtain secure data encryption or key distribution over a fiber-optic channel in the presence of an eavesdropper. In this paper we focus on the cryptographic aspects of AlphaEta and its variants. Moreover, we propose a new protocol for which we can provide a rigorous proof that the eavesdropper obtains neglible information. In comparison to single-photon quantum cryptography, AlphaEta provide much higher throughputs combined with a well-known technology.

In 2013, Sun et al. showed that the related works' authentication schemes proposed by [2-7] are vulnerable to an insider attack and fail to provide mutual authentication. These two attacks can be successfully plotted by an adversary, since the private key of the server can compute all the legal users’ private keys. They then proposed a new remote user authentication and key agreement scheme for the mobile client-server environment. However, we find that their scheme is still vulnerable to insider attack (Sun et al.) and how to avoid such an insider attack on the client-server environment is still an open problem.

The UMTS/LTE protocol for mobile phone networks has been designed to offer a limited form of anonymity for mobile phone uses. In this paper we quantify precisely what this limited form of anonymity actually provides via a formal security model. The model considers an execution where the home and roaming network providers are considered as one entity. We consider two forms of anonymity, one where the mobile stations under attacked are statically selected before the execution, and a second one where the adversary selects these stations adaptively. We prove that the UMTS/LTE protocol meets both of these security definitions. Our analysis requires new assumptions on the underlying keyed functions for UMTS, which whilst probably true have not previously been brought to the fore.

In a mobile environment, a number of users act as a network nodes and communicate with one another to acquire location based information and services. This emerging paradigm has opened up new business opportunities and enables numerous applications such as road safety enhancement, service recommendations and mobile entertainment. A fundamental issue that impacts the success of these applications is the security and privacy concerns raised regarding the mobile users. In that, a malicious user or service provider can track the locations of a user traveled so that other malicious act can be carried out more effectively against the user. Therefore, the challenge becomes how to authenticate mobile users while preserving their actual identity and location privacy. In this work, we propose a novel randomized or privacy-preserving authentication protocol based on homomorphic encryption. The protocol allows individual users to self generate any number of authenticated identities to achieve full anonymity in mobile environment. The proposed protocol prevents users being tracked by any single party including peer users, service providers, authentication servers, and other infrastructure. Meanwhile, our protocol also provides traceability in case of any dispute. We have conducted experimental study which demonstrates the efficiency of our protocol. Another advantage of the proposed protocol is lightweight computation and storage requirement, particularly suitable for any mobile devices with limited computation power and storage space.

Sound reasoning about the behavior of programs relies on program execution adhering to the language semantics. However, in a distributed computation, when a value is sent from one party to another, the receiver faces the question of whether the value is well-traced: could it have been produced by a computation that respects the language semantics? If not, then accepting the non-well-traced value may invalidate the receiver's reasoning, leading to bugs or vulnerabilities. Proof-Carrying Data (PCD) is a recently-introduced cryptographic mechanism that allows messages in a distributed computation to be accompanied by proof that the message, and the history leading to it, complies with a specified predicate. Using PCD, a verifier can be convinced that the predicate held throughout the distributed computation, even in the presence of malicious parties, and at a verification cost that is independent of the size of the computation producing the value. Unfortunately, previous approaches to using PCD required tailoring a specialized predicate for each application, using an inconvenient formalism and with little methodological support. We connect these two threads by introducing a novel, PCD-based approach to enforcing language semantics in distributed computations. We show how to construct an object-oriented language runtime that ensures that objects received from potentially untrusted parties are well-traced with respect to a set of class definitions. Programmers can then soundly reason about program behavior, despite values received from untrusted parties, without needing to be aware of the underlying cryptographic techniques.

Internet voting continues to enjoy wide interest from both research and practice. Among the Internet voting schemes developed over the last decades, JCJ / Civitas stands out from the masses due to its innovative approach to resist voter coercion. To achieve its ambitious goal, the scheme builds upon particularly restrictive assumptions and an abstract credential handling rendering the scheme impractical for real-world use. At ARES 2012, Neumann and Volkamer presented a proposal which implements several of these assumptions (voter-side assumptions) and the credential handling by the use of smart cards. While addressing these practical shortcomings of JCJ / Civitas, their proposal did not take performance into account, and accordingly its performance has not been evaluated. In the present work, we revise the ARES proposal from a performance perspective in a security-invariant manner. Based on the herein proposed revisions, we are able to conclude that the revised ARES proposal is feasible to be used in real-world elections.

Electronic voting systems are among the most security critical distributed systems. Different trust concepts are implemented to mitigate the risk of conspiracies endangering security properties. These concepts render systems often very complex and end users no longer recognize whom they need to trust. Correspondingly, specific trust considerations are necessary to support users. Recently, resilience terms have been proposed in order to express, which entities can violate the addressed security properties in particular by illegal collaborations. However, previous works derived these resilience terms manually. Thus, successful attacks can be missed. Based on this approach, we propose a framework to formally and automatically derive these terms. Our framework comprises a knowledge calculus, which allows us to model knowledge and reason about knowledge of collaborating election entities. The introduced framework is applied to deduce previously manually derived resilience terms of three remote electronic voting systems, namely Polyas, Helios and the Estonian voting system. Thereby, we were able to discover mistakes in previous derivations.

The enforcement of sensitive policies in untrusted environments is still an open challenge for policy-based systems. On the one hand, taking any appropriate security decision requires access to these policies. On the other hand, if such access is allowed in an untrusted environment then confidential information might be leaked by the policies. The key challenge is how to enforce sensitive policies and protect content in untrusted environments. In the context of untrusted environments, we mainly distinguish between outsourced and distributed environments. The most attractive paradigms concerning outsourced and distributed environments are cloud computing and opportunistic networks, respectively. In this dissertation, we present the design, technical and implementation details of our proposed policy-based access control mechanisms for untrusted environments. First of all, we provide full confidentiality of access policies in outsourced environments, where service providers do not learn private information about policies during the policy deployment and evaluation phases. Our proposed architecture is such that we are able to support expressive policies and take into account contextual information before making any access decision. The system entities do not share any encryption keys and even if a user is deleted, the system is still able to perform its operations without requiring any action. For complex user management, we have implemented a policy-based Role-Based Access Control (RBAC) mechanism, where users are assigned roles, roles are assigned permissions and users execute permissions if their roles are active in the session maintained by service providers. Finally, we offer the full-fledged RBAC policies by incorporating role hierarchies and dynamic security constraints. In opportunistic networks, we protect content by specifying expressive access control policies. In our proposed approach, brokers match subscriptions against policies associated with content without compromising privacy of subscribers. As a result, an unauthorised broker neither gains access to content nor learns policies and authorised nodes gain access only if they satisfy fine-grained policies specified by publishers. Our proposed system provides scalable key management in which loosely-coupled publishers and subscribers communicate without any prior contact. Finally, we have developed a prototype of the system that runs on real smartphones and analysed its performance.

The steadily growing number of certification authorities (CAs) assigned to the Web Public Key Infrastructure (Web PKI) and trusted by current browsers imposes severe security issues. Apart from being impossible for relying entities to assess whom they actually trust, the current binary trust model implemented with the Web PKI makes each CA a single point of failure. In this paper, we present the concept of trust views to manage variable trust levels for exactly those CAs actually required by a relying entity. This reduces the set of trusted CAs and minimizes the risk to rely on malicious certificates issued due to CA failures or compromises.

Keyless Signatures Infrastructure (KSI) is a globally distributed system for providing time-stamping and server-supported digital signature services. Global per-second hash trees are created and their root hash values published. We discuss some service quality issues that arise in practical implementation of the service and present solutions for avoiding single points of failure and guaranteeing a service with reasonable and stable delay. Guardtime AS has been operating a KSI Infrastructure for 5 years. We summarize how the KSI Infrastructure is built, and the lessons learned during the operational period of the service.

In this paper we address the problem of authenticated query processing in outsourced databases. An authenticated query processing mechanism allows a client to verify the validity of the query responses that it gets from an untrusted and remote server, who stores the client's database on its behalf. We introduce a general framework called RDAS for the problem of authenticated query processing, and define the security goals for this task in line with concrete provable security. We propose several schemes which enable a client to verify both the completeness and correctness of the query responses of a server. All the schemes follow the proposed framework and are provably secure in terms of the proposed security definition. The novelty of the proposed schemes is that they use bitmap indexes as a main component for providing authentication. Bitmap indexes have recently seen lot of applications for accelerated query processing and many commercial databases implement such indexes. Bitmaps have not been previously used for a security goal. We show that the proposed schemes can match in both functionality and efficiency compared to the existing schemes. We also implement the schemes on a real database and provide extensive experimental studies on the schemes

We investigate an application of Radio Frequency Identification (RFID) referred to in the literature as group scanning, in which an RFID reader device interrogates several RFID tags to establish “simultaneous” presence of a group of tags. Our goal is to study the group scanning problem in strong adversarial settings and show how group scanning can be used in distributed applications for supply chain management. We present a security framework for group scanning and give a formal description of the attending security requirements. Our model is based on the Universal Composability framework and supports re-usability (through modularity of security guarantees). We propose two novel protocols that realize group scanning in this security model, based on off-the-shelf components such as low-cost (highly optimized) pseudorandom functions, and show how these can be integrated into RFID supply-chain management systems

Physical authentication brings extra security to software authentication by adding real-world input to conventional authentication protocols. Existing solutions such as textual and graphical passwords are subject to brute force and shoulder surfing attacks, while users are reluctant to use biometrics for identification, due to its intrusiveness. This paper uses Hamiltonian tokens as authentication means. The proposed token structure offers many possible configurations ({\sl i.e.}, passwords) and is small enough to be carried on a physical keychain. After presenting our general idea, we describe an efficient algorithm to produce these tokens. Our procedure was validated by running a recognition campaign on a wide batch of synthetic samples, and experimented on prototypes manufactured using a commercial 3D-printer.

Encrypting information has been regarded as one of the most substantial approaches to protect users’ sensitive information in radically changing internet technology era. In prior research, researchers have considered similarity search over encrypted documents infeasible, because the single-bit difference of a plaintext would result in an enormous bits difference in the corresponding ciphertext. However, we propose a novel idea of Security Similarity Search (SSS) over encrypted documents by applying character-wise encryption with approximate string matching to keyword index search systems. In order to do this, we define the security requirements of similarity search over encrypted data, propose two similarity search schemes, and formally prove the security of the schemes. The first scheme is more efficient, while the second scheme achieves perfect similarity search privacy. Surprisingly, the second scheme turns out to be faster than other keyword index search schemes with keywordwise encryption, while enjoying the same level of security. The schemes of SSS support “like query(‘ab%’)” and a query with misprints in that the character-wise encryption preserves the degree of similarity between two plaintexts, and renders approximate string matching between the corresponding ciphertexts possible without decryption.

With over 1.6~billion debit and credit cards in use worldwide, the EMV system (a.k.a. ``Chip-and-PIN'') has become one of the most important deployed cryptographic protocol suites. Recently, the EMV consortium has decided to upgrade the existing RSA based system with a new system relying on Elliptic Curve Cryptography (ECC). One of the central components of the new system is a protocol that enables a card to establish a secure channel with a card reader. In this paper we provide a security analysis of the proposed protocol, we propose minor changes/clarifications to the ``Request for Comments'' issued in Nov 2012, and demonstrate that the resulting protocol meets the intended security goals. The structure of the protocol is one commonly encountered in practice: first run a key-exchange to establish a shared key (which performs authentication and key confirmation), only then use the channel to exchange application messages. Although common in practice, this structure takes the protocol out of the reach of most standard security models for key-exchange. Unfortunately, the only models that can cope with the above structure suffer from some drawbacks that make them unsuitable for our analysis. Our second contribution is to provide new security models for channel establishment protocols. Our models have a more inclusive syntax, are quite general, deal with a realistic notion of authentication (one-sided authentication as required by EMV), and do not suffer from the drawbacks that we identify in prior models.

In this paper we propose a method which will preserve sum- mary statistics of data organized in a two way table. We have shown that fully homomorphic encryption is a powerful solution. However it has a number of disadvantages which makes it impractical. We have proposed a Restricted homomorphic encryption method which uses Pailier encryp- tion and order preserving encryption. This new method can be used for practical purposes owing to it’s efficiency in terms of both speed and storage.

Physical Unclonable Functions (PUFs) are increasingly becoming a well-known security primitive for secure key storage and anti-counterfeiting. For both applications it is imperative that PUFs provide enough entropy. The aim of this paper is to propose a new model for binary-output PUFs such as SRAM, DFF, Latch and Buskeeper PUFs, and a method to accurately estimate their entropy. In our model the measurable property of a PUF is its set of cell biases. We determine an upper bound on the ‘extractable entropy’, i.e. the number of key bits that can be robustly extracted, by calculating the mutual information between the bias measurements done at enrollment and reconstruction. In previously known methods only uniqueness was studied using information-theoretic measures, while robustness was typically expressed in terms of error probabilities or distances. It is not always straightforward to use a combination of these two metrics in order to make an informed decision about the performance of different PUF types. Our new approach has the advantage that it simultaneously captures both of properties that are vital for key storage: uniqueness and robustness. Therefore it will be possible to fairly compare performance of PUF implementations using our new method. Statistical validation of the new methodology shows that it clearly captures both of these properties of PUFs. In other words: if one of these aspects (either uniqueness or robustness) is less than optimal, the extractable entropy decreases. Analysis on a large database of PUF measurement data shows very high entropy for SRAM PUFs, but rather poor results for all other memory-based PUFs in this database.

Deep packet inspection (DPI) technologies provide much-needed visibility and control of network traffic using port-independent protocol identification, where a network flow is labeled with its application-layer protocol based on packet contents. In this paper, we provide the first comprehensive evaluation of a large set of DPI systems from the point of view of protocol misidentification attacks, in which adversaries on the network attempt to force the DPI to mislabel connections. Our approach uses a new cryptographic primitive called format-transforming encryption (FTE), which extends conventional symmetric encryption with the ability to transform the ciphertext into a format of our choosing. We design an FTE-based record layer that can encrypt arbitrary application-layer traffic, and we experimentally show that this forces misidentification for all of the evaluated DPI systems. This set includes a proprietary, enterprise-class DPI system used by large corporations and nation-states. We also show that using FTE as a proxy system incurs no latency overhead and as little as 16\% bandwidth overhead compared to standard SSH tunnels. Finally, we integrate our FTE proxy into the Tor anonymity network and demonstrate that it evades real-world censorship by the Great Firewall of China.

The increasing penetration of Online Social Networks (OSNs) prompts the need for effectively accessing and utilizing social networking information. In numerous applications, users need to make trust and/or access control decisions involving other (possibly stranger) users, and one important factor is often the existence of common social relationships. This motivates the need for secure and privacy-preserving techniques allowing users to assess whether or not they have mutual friends. This paper introduces the Common Friends service, a framework for finding common friends which protects privacy of non-mutual friends and guarantees authenticity of friendships. First, we present a generic construction that reduces to secure computation of set intersection, while ensuring authenticity of announced friends via bearer capabilities. Then, we propose an efficient instantiation, based on Bloom filters, that only incurs a constant number of public-key operations and appreciably low communication overhead. Our software is designed so that developers can easily integrate Common Friends into their applications, e.g., to enforce access control based on users' social proximity in a privacy-preserving manner. Finally, we showcase our techniques in the context of an existing application for sharing (tethered) Internet access, whereby users decide to share access depending on the existence of common friends. A comprehensive experimental evaluation attests to the practicality of proposed techniques.

One of the most challenging aspects in computer-supported voting is to combine the apparently conflicting requirements of privacy and verifiability. On the one hand, privacy requires that a vote cannot be traced back from the result to a voter, while on the other hand, verifiability states that a voter can trace the effect of her vote on the result. This can be addressed using various privacy-enabling cryptographic primitives which also offer verifiability. As more and more refined voting systems were proposed, understanding of first privacy and later verifiability in voting increased, and notions of privacy as well as notions of verifiability in voting became increasingly more refined. This has culminated in a variety of verifiable systems that use cryptographic primitives to ensure specific kinds of privacy. However, the corresponding privacy and verifiability claims are not often verified independently. When they are investigated, claims have been invalidated sufficiently often to warrant a cautious approach to them. The multitude of notions, primitives and proposed solutions that claim to achieve both privacy and verifiability form an interesting but complex landscape. The purpose of this paper is to survey this landscape by providing an overview of the methods, developments and current trends regarding privacy and verifiability in voting systems.

Proof-of-retrievability schemes have been a topic of considerable recent interest. In these schemes, a client gives a file M to a server with the understanding that the server will securely store M. A suitable challenge-response protocol is invoked by the client in order for the client to gain confidence that M is indeed being correctly stored by the server. The definition of proof-of-retrievability schemes is based on the notion of an extractor that can recover the file once the challenge-response protocol is executed a sufficient number of times. In this paper, we propose a new type of scheme that we term a proof-of-data-observability scheme. Our definition tries to capture the stronger requirement that the server must have an actual copy of M in its memory space while it executes the challenge-response protocol. We give some examples of schemes that satisfy this new security definition. As well, we analyze the efficiency and security of the protocols we present, and we prove some necessary conditions for the existence of these kinds of protocols.

Data outsourcing is a growing business model offering services to individuals and enterprises for processing and storing a huge amount of data. It is not only economical but also promises higher availability, scalability, and more effective quality of service than in-house solutions. Despite all its benefits, data outsourcing raises serious security concerns for preserving data confidentiality. There are solutions for preserving confidentiality of data while supporting search on the data stored in outsourced environments. However, such solutions do not support access policies to regulate access to a particular subset of the stored data. For complex user management, large enterprises employ Role-Based Access Controls (RBAC) models for making access decisions based on the role in which a user is active in. However, RBAC models cannot be deployed in outsourced environments as they rely on trusted infrastructure in order to regulate access to the data. The deployment of RBAC models may reveal private information about sensitive data they aim to protect. In this paper, we aim at filling this gap by proposing ESPOON ERBAC for enforcing RBAC policies in outsourced environments. ESPOON ERBAC enforces RBAC policies in an encrypted manner where a curious service provider may learn a very limited information about RBAC policies. We have implemented ESPOON ERBAC and provided its performance evaluation showing a limited overhead, thus confirming viability of our approach.

Short-range wireless communication technologies have been used in many security-sensitive smartphone applications and services such as contactless micro payment and device pairing. Typically, the data confidentiality of the existing short-range communication systems relies on so-called "key-exchange then encryption" mechanism. Namely, both parties need to spend extra communication to establish a common key before transmitting their actual messages, which is inefficient, especially for short communication sessions. In this work, we present PriWhisper -- a keyless secure acoustic short-range communication system for smartphones. It is designed to provide a purely software-based solution to secure smartphone short-range communication without the key agreement phase. PriWhisper adopts the emerging friendly jamming technique from radio communication for data confidentiality. The system prototype is implemented and evaluated on several Android smartphone platforms for efficiency and usability. We theoretically and experimentally analyze the security of our proposed acoustic communication system against various passive and active adversaries. In particular, we also study the (in)separability of the data signal and jamming signal against Blind Signal Segmentation (BSS) attacks such as Independent Component Analysis (ICA). The result shows that PriWhisper provides sufficient security guarantees for commercial smartphone applications and yet strong compatibilities with most legacy smartphone platforms.

Criteria based on the analysis of the properties of vectorial Boolean functions for selection of substitutions (S-boxes) for symmetric cryptographic primitives are given. We propose an improved gradient descent method for increasing performance of nonlinear vectorial Boolean functions generation with optimal cryptographic properties. Substitutions are generated by proposed method for the most common 8-bits input and output messages have nonlinearity 104, 8-uniformity and algebraic immunity 3.

Software attestation has become a popular and challenging research topic at many established security conferences with an expected strong impact in practice. It aims at verifying the software integrity of (typically) resource-constrained embedded devices. However, for practical reasons, software attestation cannot rely on stored cryptographic secrets or dedicated trusted hardware. Instead, it exploits side-channel information, such as the time that the underlying device needs for a specific computation. As traditional cryptographic solutions and arguments are not applicable, novel approaches for the design and analysis are necessary. This is certainly one of the main reasons why the security goals, properties and underlying assumptions of existing software attestation schemes have been only vaguely discussed so far, limiting the confidence in their security claims. Thus, putting software attestation on a solid ground and having a founded approach for designing secure software attestation schemes is still an important open problem. We provide the first steps towards closing this gap. Our first contribution is a security framework that formally captures security goals, attacker models, and various system and design parameters. Moreover, we present a generic software attestation scheme that covers most existing schemes in the literature. Finally, we analyze its security within our framework, yielding sufficient conditions for provably secure software attestation schemes. We expect that such a consolidating work allows for a meaningful security analysis of existing schemes and supports the design of arguably secure software attestation schemes and will inspire new research in this area.

A (k; n) threshold secret image sharing scheme, abbreviated as (k; n)-TSISS, splits a secret image into n shadow images in such a way that any k shadow images can be used to reconstruct the secret image exactly. In 2002, for (k; n)-TSISS, Thien and Lin reduced the size of each shadow image to 1/k of the original secret image. Their main technique is by adopting all coefficients of a (k-1)-degree polynomial to embed the secret pixels. This benet of small shadow size has drawn many researcher's attention and their technique has been extensively used in the following studies. In this paper, we rst show that this technique is neither information theoretic secure nor computational secure. Furthermore, we point out the security defect of previous (k; n)-TSISSs for sharing textual images, and then fix up this security defect by adding an AES encryption process. At last, we prove that this new (k; n)-TSISS is computational secure.

Mechanisms for secure mobile communication can be enablers for novel applications in the area of cooperative work. In this context, this article exemplarily investigates an emergency management setting. An efficient support of emergency communication is of high practical importance, but has specific challenges: unpredictable local crisis situations harden the establishment of communication structures, legal requirements dictate the use of end-to-end secure and documentable approaches, while end users demand user-friendliness and privacy protection. Dealing with these challenges, the contribution of this article is two-fold. Firstly, together with emergency practioners, we follow a participatory design approach. We define security requirements, patterns for efficient communication and derive a design proposal. Secondly, we devise a novel approach to multilaterally end-to-end secure, user-friendly attribute-based messaging for one-to-many communication. It builds on a hybrid encryption technique, which efficiently combines ciphertext-policy attribute-based encryption, location-based encryption and symmetric encryption. The hybrid encryption approach supports dynamic location attributes as user-friendly selectors for targeted messaging with dynamic groups of mobile and anonymous receivers. The achieved security of the approach and concrete application scenarios are discussed.

Distance-bounding is a practical solution to be used in security-sensitive contexts, to prevent relay attacks. Its applied cryptographic role is definitely spreading fast and it is clearly far reaching, extending from contactless payments to remote car unlocking. However, security models for distance-bounding are not well-established and, as far as we know, no existing protocol is proven to resist all classical attacks: distance-fraud, mafia-fraud, and terrorist-fraud. We herein amend the latter, whilst maintaining the lightweight nature that makes these protocols appropriate for concrete applications. Firstly, we develop a general formalism for distance-bounding protocols and their security requirements. In fact, we also propose specifications of generalised frauds, stemming from the (attack-prone) multi-party scenarios. This entails our incorporation of newly advanced threats, e.g., distance-hijacking. Recently, Boureanu et al. proposed the SKI protocol. We herein extend it and prove its security. To attain resistance to terrorist-fraud, we put forward the use of a leakage scheme and of secret sharing, which we specialise and reinforce with additional requirements. In view of resistance to generalised mafia-frauds (and terrorist frauds), we further introduce the notion of circular-keying for pseudorandom functions (PRFs); this notion models the employment of a PRF, with possible linear reuse of the key. We also identify the need of PRF masking to fix common mistakes in existing security proofs/claims of distance-fraud security. We then enhance our design such that we guarantee resistance to terrorist-fraud in the presence of noise. To our knowledge, all this gives rises the first practical and provably secure class of distance-bounding protocols, even when our protocols are run in noisy communications, which is indeed the real-life setting of deployed, time-critical cryptographic protocols.