Paper 2016/663 Original: eprint.iacr.org/2016/663 ↗

Anonymous Attestation Using the Strong Diffie Hellman Assumption Revisited

Jan Camenisch
Manu Drijvers
Anja Lehmann
Abstract

Direct Anonymous Attestation (DAA) is a cryptographic protocol for privacy-protecting authentication. It is standardized in the TPM standard and implemented in millions of chips. A variant of DAA is also used in Intel's SGX. Recently, Camenisch et al.~(PKC 2016) demonstrated that existing security models for DAA do not correctly capture all security requirements, and showed a number of flaws in existing schemes based on the LRSW assumption. In this work, we identify flaws in security proofs of a number of qSDH-based DAA schemes and point out that none of the proposed schemes can be proven secure in the recent model by Camenisch et al.~(PKC 2016). We therefore present a new, provably secure DAA scheme that is based on the qSDH assumption. The new scheme is one of the most efficient DAA schemes, with support for DAA extensions to signature-based revocation and attributes. We rigorously prove the scheme secure in the model of Camenisch et al., which we modify to support the extensions. As a side-result of independent interest, we prove that the BBS+ signature scheme is secure in the type-3 pairing setting, allowing for our scheme to be used with the most efficient pairing-friendly curves.

Metadata
Available format(s)
PDF
Category
Cryptographic protocols
Publication info
Preprint.
History
2017-01-06: last updated
2016-06-28: published
Short URL
https://ia.cr/2016/663
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2016/663,
      author = {Jan Camenisch and Manu Drijvers and Anja Lehmann},
      title = {Anonymous Attestation Using the Strong Diffie Hellman Assumption Revisited},
      howpublished = {Cryptology {ePrint} Archive, Paper 2016/663},
      year = {2016},
      url = {https://eprint.iacr.org/2016/663}
}
Note: In order to protect the privacy of readers, this archive does not use cookies or embedded third party content.