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Cryptanalytic time–memory trade-off for password hashing schemes

  • Donghoon Chang
  • Arpan Jati
  • Sweta Mishra
  • Somitra Kumar Sanadhya
Regular Contribution
  • 44 Downloads

Abstract

Increasing threat of password leakage from compromised password hashes demands a resource consuming password-hashing algorithm to prevent the precomputation of the password hashes. A class of password-hashing schemes (PHS) provides such a defense by making the design Memory hard. This ensures that any reduction in the memory consumed by the algorithm leads to an exponential increase in its runtime. The security offered by a memory-hard PHS design is measured in terms of its time–memory trade-off (TMTO) defense. Another important measure for a good PHS is its efficiency in utilizing all the available memory as quickly as possible, and fast running time when more than the required memory is available. In this work, we present a simple technique to analyze TMTO for a password-hashing scheme which can be represented as a directed acyclic graph (DAG). The nodes of the DAG correspond to the storage required by the algorithm and the edges correspond to the flow of the execution. Our proposed technique provides expected runtimes at varied levels of available storage utilizing the DAG representation of the algorithm. We show the effectiveness of our proposed technique by applying it on three designs from the “Password Hashing Competition" (PHC)—Argon2-Version 1.2.1 (the PHC winner), Catena-Version 3.2 and Rig-Version 2. Our analysis shows that Argon2i is not providing expected memory hardness which is also highlighted in a recent work by Corrigan-Gibbs et al. We analyze these PHS for performance under various settings of time and memory complexities. Our experimental results show (i) simple DAGs for PHS are efficient but not memory hard, (ii) complex DAGs for PHS are memory hard but less efficient, and (iii) combination of two simple graphs in the representation of a DAG for PHS achieves both memory hardness and efficiency.

Keywords

Time–memory trade-off Password Hashing Memory hard Graph traversal Bit-reversal graph Double butterfly graph 

Supplementary material

10207_2018_405_MOESM1_ESM.pdf (199 kb)
Supplementary material 1 (pdf 199 KB)
10207_2018_405_MOESM2_ESM.pdf (263 kb)
Supplementary material 2 (pdf 262 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Indraprashtha Institute of Information Technology, Delhi (IIIT-Delhi)DelhiIndia
  2. 2.Indian Institute of Technology, Ropar (IIT-Ropar)RoparIndia

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