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Genetic Algorithm as Optimization Tool for Differential Cryptanalysis of DES6

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Computational Collective Intelligence (ICCCI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10449))

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Abstract

This article presents a new differential attack on the Data Encryption Standard (DES) reduced to 6 rounds, with the usage of the genetic algorithm (GA). The objective of the proposed attack is to indicate the last encryption subkey, used in the sixth cipher round, which makes it possible to define 48 from 56 primary key bits. The remaining 8 bits may be guessed by executing a brute-force attack. An additional heuristic negation operator was introduced to improve local search of proposed algorithm named NGA. The algorithm is based on the basic techniques of differential cryptanalysis. The results of the proposed NGA attack were compared with the simple genetic algorithm (SGA) and the simulated annealing (SA) attacks.

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Author information

Authors and Affiliations

  1. University of Silesia, Sosnowiec, Poland

    Kamil Dworak & Urszula Boryczka

  2. Future Processing, Gliwice, Poland

    Kamil Dworak

Authors
  1. Kamil Dworak
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  2. Urszula Boryczka
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Corresponding author

Correspondence to Kamil Dworak .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Department of Computer Science, University of Cyprus, Nicosia, Cyprus

    George A. Papadopoulos

  3. Department of Information Systems, Gdynia Maritime University, Gdynia, Poland

    Piotr Jędrzejowicz

  4. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  5. Department of Information Systems, University of Münster, Münster, Germany

    Gottfried Vossen

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Dworak, K., Boryczka, U. (2017). Genetic Algorithm as Optimization Tool for Differential Cryptanalysis of DES6. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10449. Springer, Cham. https://doi.org/10.1007/978-3-319-67077-5_11

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  • DOI: https://doi.org/10.1007/978-3-319-67077-5_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67076-8

  • Online ISBN: 978-3-319-67077-5

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