Paper 2020/663

Super-Linear Time-Memory Trade-Offs for Symmetric Encryption

Wei Dai, Stefano Tessaro, and Xihu Zhang

Abstract

We build symmetric encryption schemes from a pseudorandom function/permutation with domain size N which have very high security -- in terms of the amount of messages q they can securely encrypt -- assuming the adversary has S<N bits of memory. We aim to minimize the number of calls k we make to the underlying primitive to achieve a certain , or equivalently, to maximize the achievable for a given . We target in particular , in contrast to recent works (Jaeger and Tessaro, EUROCRYPT '19; Dinur, EUROCRYPT '20) which aim to beat the birthday barrier with one call when . Our first result gives new and explicit bounds for the Sample-then-Extract paradigm by Tessaro and Thiruvengadam (TCC '18). We show instantiations for which . If , Thiruvengadam and Tessaro's weaker bounds only guarantee when . In contrast, here, we show this is true already for . We also consider a scheme by Bellare, Goldreich and Krawczyk (CRYPTO '99) which evaluates the primitive on independent random strings, and masks the message with the XOR of the outputs. Here, we show , using new combinatorial bounds on the list-decodability of XOR codes which are of independent interest. We also study best-possible attacks against this construction.

Metadata
Available format(s)
PDF
Category
Foundations
Publication info
Preprint. MINOR revision.
Keywords
secret-key cryptographyinformation theorypseudo-randomnessspace-time trade-offs
Contact author(s)
weidai @ eng ucsd edu
tessaro @ cs washington edu
xihu @ cs washington edu
History
2020-06-04: revised
2020-06-03: received
See all versions
Short URL
https://ia.cr/2020/663
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2020/663,
      author = {Wei Dai and Stefano Tessaro and Xihu Zhang},
      title = {Super-Linear Time-Memory Trade-Offs for Symmetric Encryption},
      howpublished = {Cryptology {ePrint} Archive, Paper 2020/663},
      year = {2020},
      url = {https://eprint.iacr.org/2020/663}
}
Note: In order to protect the privacy of readers, eprint.iacr.org does not use cookies or embedded third party content.