Fitness comparison by statistical testing in construction of SAT-based guess-and-determine cryptographic attacks

Artem Pavlenko, Maxim Buzdalov, Vladimir Ulyantsev

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

Abstract

Algebraic cryptanalysis studies breaking ciphers by solving algebraic equations. Some of the promising approaches use SAT solvers for this purpose. Although the corresponding satisfiability problems are hard, their difficulty can often be lowered by choosing a set of variables to brute force over, and by solving each of the corresponding reduced problems using a SAT solver, which is called the guess-and-determine attack. In many successful cipher breaking attempts this set was chosen analytically, however, the nature of the problem makes evolutionary computation a good choice.

We investigate one particular method for constructing guess-and-determine attacks based on evolutionary algorithms. This method estimates the fitness of a particular guessed bit set by Monte-Carlo simulations. We show that using statistical tests within the comparator of fitness values, which can be used to reduce the necessary number of samples, together with a dynamic strategy for the upper limit on the number of samples, speeds up the attack by a factor of 1.5 to 4.3 even on a distributed cluster.
Original languageEnglish
Title of host publicationGECCO '19
Subtitle of host publicationProceedings of the Genetic and Evolutionary Computation Conference
EditorsManuel López-Ibáñez
Pages312-320
Number of pages9
DOIs
Publication statusPublished - 13 Jul 2019
Externally publishedYes
EventGECCO 2019: The Genetic and Evolutionary Computation Conference - Prague, Czech Republic
Duration: 13 Jul 201917 Jul 2019
https://gecco-2019.sigevo.org

Conference

ConferenceGECCO 2019: The Genetic and Evolutionary Computation Conference
Country/TerritoryCzech Republic
CityPrague
Period13 Jul 201917 Jul 2019
Internet address

Keywords

  • algebraic cryptanalysis
  • approximate fitness evaluation
  • satisfiability problems

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