International Association for Cryptologic Research

International Association
for Cryptologic Research


Compact Ring Signatures from Learning With Errors

Rohit Chatterjee , Stony Brook University
Sanjam Garg , University of California, Berkeley and NTT Research
Mohammad Hajiabadi , University of Waterloo
Dakshita Khurana , University of Illinois Urbana-Champaign
Xiao Liang , Stony Brook University
Giulio Malavolta , Max Planck Institute for Security and Privacy
Omkant Pandey , Stony Brook University
Sina Shiehian , University of California, Berkeley and Stony Brook University
DOI: 10.1007/978-3-030-84242-0_11 (login may be required)
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Presentation: Slides
Conference: CRYPTO 2021
Abstract: Ring signatures allow a user to sign a message on behalf of a ``ring'' of signers, while hiding the true identity of the signer. As the degree of anonymity guaranteed by a ring signature is directly proportional to the size of the ring, an important goal in cryptography is to study constructions that minimize the size of the signature as a function of the number of ring members. In this work, we present the first compact ring signature scheme (i.e., where the size of the signature grows logarithmically with the size of the ring) from the (plain) learning with errors (LWE) problem. The construction is in the standard model and it does not rely on a trusted setup or on the random oracle heuristic. In contrast with the prior work of Backes \etal~[EUROCRYPT'2019], our scheme does not rely on bilinear pairings, which allows us to show that the scheme is post-quantum secure assuming the quantum hardness of LWE. At the heart of our scheme is a new construction of compact and statistically witness-indistinguishable ZAP arguments for NP $\cap$ coNP, that we show to be sound based on the plain LWE assumption. Prior to our work, statistical ZAPs (for all of NP) were known to exist only assuming \emph{sub-exponential} LWE. We believe that this scheme might find further applications in the future.
Video from CRYPTO 2021
  title={Compact Ring Signatures from Learning With Errors},
  author={Rohit Chatterjee and Sanjam Garg and Mohammad Hajiabadi and Dakshita Khurana and Xiao Liang and Giulio Malavolta and Omkant Pandey and Sina Shiehian},