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Indifferentiability Characterization of Hash Functions and Optimal Bounds of Popular Domain Extensions

  • Rishiraj Bhattacharyya
  • Avradip Mandal
  • Mridul Nandi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5922)

Abstract

Understanding the principle behind designing a good hash function is important. Nowadays it is getting more importance due to the current SHA3 competition which intends to make a new standard for cryptogrpahic hash functions. Indifferentiability, introduced by Maurer et al in TCC’04, is an appropriate notion for modeling (pseudo)random oracles based on ideal primitives. It also gives a strong security notion for hash-designs. Since then, we know several results providing indifferentiability upper bounds for many hash-designs. Here, we introduce a unified framework for indifferentiability security analysis by providing an indifferentiability upper bound for a wide class of hash designs GDE or generalized domain extension. In our framework, we present an unified simulator and avoid the problem of defining different simulators for different constructions. We show, the probability of some bad event (based on interaction of the attacker with the GDE and the underlying ideal primitve) is actually an upper bound for indifferentiable security. As immediate applications of our result, we provide simple and improved (in fact optimal) indifferentiability upper bounds for HAIFA and tree (with counter) mode of operations. In particular, we show that n-bit HAIFA and tree-hashing with counter have optimal indifferentiability bounds \({\it \Theta}(q\sigma/2^n)\) and \({\it \Theta}(q^2 \log \ell/2^n)\) respectively, where ℓ is the maximum number of blocks in a single query and σ is the total number of blocks in all q queries made by the distinguisher.

Keywords

Indifferentiability Merkle-Damgård  HAIFA Tree mode of operations with counter 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Rishiraj Bhattacharyya
    • 1
  • Avradip Mandal
    • 2
  • Mridul Nandi
    • 3
  1. 1.Applied Statistics UnitIndian Statistical InstituteKolkataIndia
  2. 2.Université du LuxembourgLuxembourg
  3. 3.NISTUSA

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