Robust Distributed Pseudorandom Functions for mNP Access Structures
Paper in proceedings, 2019

© 2019, Springer Nature Switzerland AG. Distributed pseudorandom functions (DPRFs) formally defined by Naor et al. (EUROCRYPT’99) provide the properties of regular PRFs as well as the ability to distribute the evaluation of the PRF function; rendering them useful against single point of failures in multiple settings (e.g., key distribution centres). To avoid the corruption of the partial PRF values computed by distributed servers, Naor et al. proposed the notion of robust distributed PRFs, which not only allows the evaluation of the PRF value by a set of distributed servers, but also allows to verify if the partial evaluation values are computed correctly. In this paper, we investigate different approaches to build non-interactive robust distributed PRFs for a general class of access structures, going beyond the existing threshold and monotone span programs (MSP). More precisely, our contributions are two fold: (i) we first adapt the notion of single round robust distributed PRFs for threshold access structures to one for any mNP access structure (monotone functions in NP), and (ii) we provide a provably secure general construction of robust distributed PRFs by employing puncturable PRFs, a non-interactive witness indistinguishable proof (NIWI) and indistinguishable obfuscation. We compare our robust DPRF with existing DPRFs in terms of security guarantees, underlying assumptions and required primitives.

Monotone functions

Threshold access structures

Puncturable PRFs

Robust distributed PRFs

Author

Bei Liang

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Aikaterini Mitrokotsa

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 11723 LNCS 107-126

22nd International Conference on Information Security, ISC 2019
New York City, USA,

Subject Categories

Other Computer and Information Science

Probability Theory and Statistics

Computer Science

DOI

10.1007/978-3-030-30215-3_6

More information

Latest update

11/7/2019