Paper 2023/1424 Original: eprint.iacr.org/2023/1424 ↗

PRIVATON - Privacy Preserving Automaton for Proof of Computations

Bala Subramanyan
Abstract

Amid the landscape of confidential computing, where security and privacy reign supreme, PRIVATON emerges as a pioneering and practical solution to safeguard sensitive data and computations. A verifiable proof of computation model, with one of its variant built upon the dual sandbox strategy, PRIVATON combines Trusted Execution Environment (TEE) technologies with WebAssembly (WASM) runtime environments to establish an ecosystem for privacy-preserving computations. This approach involves fine grained modeling of computations as finite state automatons, guided by verifiable proofs that attest to their unerring execution. PRIVATON is guided by the profound principles of "least privilege" and "intentional use." Through the former, each computation module's privileges are meticulously constrained, reducing vulnerability vectors. The latter ensures that privileges are allocated explicitly, fostering comprehension and security. This rigorous adherence minimizes privilege misuse and information leakage, bolstering the overall security posture. At its core, PRIVATON's innovation lies in its comprehensive assurance of data privacy and security. State machine proofs not only attest to the absence of data leakage but also prevent unauthorized data transmission. By providing unassailable proof of computation integrity, PRIVATON shields against code misuse within the system. This proactive stance fortifies its mission to safeguard the sanctity of data, computations, and the privacy of all stakeholders. Evidenced by its real-world application, PRIVATON has been validated within the cryptocurrency trading ecosystem, where it acts as a distributed and privacy-preserving credit oracle. Its implementation within Credora’s landscape underlines its potential to transform data-centric paradigms, empowering stakeholders with an unshakeable confidence in data security. In a world where data privacy is paramount, PRIVATON stands as a guardian, epitomizing the convergence of technology, security, and trust.

Metadata
Available format(s)
PDF
Category
Applications
Publication info
Preprint.
History
2023-09-20: last updated
2023-09-20: published
Short URL
https://ia.cr/2023/1424
License
https://creativecommons.org/licenses/by-nc-nd/4.0/

BibTeX

@misc{cryptoeprint:2023/1424,
      author = {Bala Subramanyan},
      title = {PRIVATON - Privacy Preserving Automaton for Proof of Computations},
      howpublished = {Cryptology {ePrint} Archive, Paper 2023/1424},
      year = {2023},
      url = {https://eprint.iacr.org/2023/1424}
}
Note: In order to protect the privacy of readers, this archive does not use cookies or embedded third party content.