Correlated-Input Secure Hash Functions

  • Vipul Goyal
  • Adam O’Neill
  • Vanishree Rao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6597)

Abstract

We undertake a general study of hash functions secure under correlated inputs, meaning that security should be maintained when the adversary sees hash values of many related high-entropy inputs. Such a property is satisfied by a random oracle, and its importance is illustrated by study of the “avalanche effect,” a well-known heuristic in cryptographic hash function design. One can interpret “security” in different ways: e.g., asking for one-wayness or that the hash values look uniformly and independently random; the latter case can be seen as a generalization of correlation-robustness introduced by Ishai et al. (CRYPTO 2003). We give specific applications of these notions to password-based login and efficient search on encrypted data. Our main construction achieves them (without random oracles) for inputs related by polynomials over the input space (namely ℤp), based on corresponding variants of the q-Diffie Hellman Inversion assumption. Additionally, we show relations between correlated-input secure hash functions and cryptographic primitives secure under related-key attacks. Using our techniques, we are also able to obtain a host of new results for such related-key attack secure cryptographic primitives.

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Copyright information

© International Association for Cryptologic Research 2011

Authors and Affiliations

  • Vipul Goyal
    • 1
  • Adam O’Neill
    • 2
  • Vanishree Rao
    • 3
  1. 1.Microsoft ResearchIndia
  2. 2.University of TexasAustinUSA
  3. 3.University of CaliforniaLos AngelesUSA

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