International Association for Cryptologic Research

International Association
for Cryptologic Research

CryptoDB

Paper: Tight Leakage-Resilient CCA-Security from Quasi-Adaptive Hash Proof System

Authors:
Shuai Han
Shengli Liu
Lin Lyu
Dawu Gu
Download:
DOI: 10.1007/978-3-030-26951-7_15
Search ePrint
Search Google
Abstract: We propose the concept of quasi-adaptive hash proof system (QAHPS), where the projection key is allowed to depend on the specific language for which hash values are computed. We formalize leakage-resilient(LR)-ardency for QAHPS by defining two statistical properties, including LR-$$\langle \mathscr {L}_0, \mathscr {L}_1 \rangle $$-universal and LR-$$\langle \mathscr {L}_0, \mathscr {L}_1 \rangle $$-key-switching.We provide a generic approach to tightly leakage-resilient CCA (LR-CCA) secure public-key encryption (PKE) from LR-ardent QAHPS. Our approach is reminiscent of the seminal work of Cramer and Shoup (Eurocrypt’02), and employ three QAHPS schemes, one for generating a uniform string to hide the plaintext, and the other two for proving the well-formedness of the ciphertext. The LR-ardency of QAHPS makes possible the tight LR-CCA security. We give instantiations based on the standard k-Linear (k-LIN) assumptions over asymmetric and symmetric pairing groups, respectively, and obtain fully compact PKE with tight LR-CCA security. The security loss is $${{O}}(\log {Q_{{e}}})$$ where $${Q_{{e}}}$$ denotes the number of encryption queries. Specifically, our tightly LR-CCA secure PKE instantiation from SXDH has only 4 group elements in the public key and 7 group elements in the ciphertext, thus is the most efficient one.
Video from CRYPTO 2019
Video provided under Creative Commons / CC BY 3.0
BibTeX
@article{crypto-2019-29894,
  title={Tight Leakage-Resilient CCA-Security from Quasi-Adaptive Hash Proof System},
  booktitle={Advances in Cryptology – CRYPTO 2019},
  series={Lecture Notes in Computer Science},
  publisher={Springer},
  volume={11693},
  pages={417-447},
  doi={10.1007/978-3-030-26951-7_15},
  author={Shuai Han and Shengli Liu and Lin Lyu and Dawu Gu},
  year=2019
}