Genetic Cryptanalysis

  • Abdelwadood Mesleh
  • Bilal Zahran
  • Anwar Al-Abadi
  • Samer Hamed
  • Nawal Al-Zabin
  • Heba Bargouthi
  • Iman Maharmeh
Part of the Communications in Computer and Information Science book series (CCIS, volume 87)

Abstract

In this work, Elitism Genetic Algorithm cryptanalysis for the basic substitution permutation network is implemented. The GA cryptanalysis algorithm gets the entire key bits. Results show the robustness of the proposed GA cryptanalysis algorithm.

Keywords

Cryptanalysis Elitism GA 

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References

  1. 1.
    Stallings, W.: Cryptography and Network Security Principles and Practices, 4th edn. Prentice Hall, Englewood Cliffs (2005)Google Scholar
  2. 2.
    Biham, E., Shamir, A.: Differential cryptanalysis of DES-like cryptosystems. Journal of cryptography 4(1), 3–72 (1991)MATHMathSciNetGoogle Scholar
  3. 3.
    Matsui, M.: Linear cryptanalysis method for DES cipher. In: Helleseth, T. (ed.) EUROCRYPT 1993. LNCS, vol. 765, pp. 386–397. Springer, Heidelberg (1994)Google Scholar
  4. 4.
    Goldberg, D.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Publishing Company Inc., Reading (1989)MATHGoogle Scholar
  5. 5.
    Albassal, A., Wahdan, A.: Genetic algorithm cryptanalysis of the basic substitution permutation network. In: Proceedings of the 2003 IEEE Midwest International Symposium on Circuits and Systems (MWSCAS ’03), December 2003. IEEE, Los Alamitos (2003)Google Scholar
  6. 6.
    Hernández-Castro, J., Isasi, P.: New results on the genetic cryptanalysis of TEA and reduced round versions of XTEA. In: Proceedings of the 2004 IEEE Congress on Evolutionary Computation (CEC 2004), June 2004, vol. 2(2), pp. 2124–2129 (2004)Google Scholar
  7. 7.
    Dozier, G., Garrett, A., Hamilton, J.: A comparison of genetic algorithm techniques for the cryptanalysis of TEA. International Journal of Intelligent Control and Systems (IJICS) 12(4), 325–330 (2007)Google Scholar
  8. 8.
    Toemeh, R., Arumugam, S.: Applying Genetic Algorithms for Searching Key-Space of Polyalphabetic Substitution Ciphers. The International Arab Journal of Information Technology 5(1) (January 2008)Google Scholar
  9. 9.
    Bergmann, K., Jacob, C., Scheidler, R.: Cryptanalysis using genetic algorithms. In: Keijzer, M. (ed.) Proceedings of the 2008 Genetic and Evolutionary Computation Conference (GECCO 2008), July 2008, pp. 1099–1100 (2008)Google Scholar
  10. 10.
    Gorodilov, A., Morozenko, V.: Genetic Algorithm for finding the keys length and cryptanalysis of the permutation cipher. International Journal Information Theories & Applications 15, 94–99 (2008)Google Scholar
  11. 11.
    Husei, H., Bayoumi, B.: A Genetic Algorithm for Cryptanalysis with Application to DES-like Systems. International Journal of Network Security 8(2), 177–186 (2009)Google Scholar
  12. 12.
    Heys, H.: A Tutorial on Linear and Differential Cryptanalysis, Technical Report CORR 2001-17, Centre for Applied Cryptographic Research, Department of Combinatorics and Optimization, University of Waterloo (March 2001); Also appears in Cryptologia, vol. XXVI(3), pp. 189–221 (2002)Google Scholar
  13. 13.
    Shannon, C.: Communication theory of secrecy systems. Bell System Technical Journal 28, 656–715 (1949)MATHMathSciNetGoogle Scholar
  14. 14.
    Feistel, H.: Cryptography and computer privacy. Scientific American 228(5), 15–23 (1973)CrossRefGoogle Scholar
  15. 15.
    Kam, J., Davida, G.: A structured design of substitution-permutation encryption networks. IEEE Transactions on Computers 28(10), 747–753 (1979)MATHCrossRefMathSciNetGoogle Scholar
  16. 16.
    O’Connor, L.: On the distribution of characteristics in bijective mappings. In: Helleseth, T. (ed.) EUROCRYPT 1993. LNCS, vol. 765, pp. 360–370. Springer, Heidelberg (1994)Google Scholar
  17. 17.
    Heys, H., Tavares, S.: The design of product ciphers resistant to differential and linear cryptanalysis. In: Stinson, D.R. (ed.) CRYPTO 1993. LNCS, vol. 773. Springer, Heidelberg (1994)Google Scholar
  18. 18.
    Reed, P., Minsker, B., Goldberg, D.: The practitioner’s role in competent search and optimization using genetic algorithms. Presented at the World Water and Environmental Resources Congress, Washington, DC (2001)Google Scholar
  19. 19.
    Rogers, A., Bennett, A.: Genetic drift in genetic algorithm selection schemes. IEEE Transaction Evolutionary Computation 3, 298–303 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Abdelwadood Mesleh
    • 1
  • Bilal Zahran
    • 1
  • Anwar Al-Abadi
    • 1
  • Samer Hamed
    • 1
  • Nawal Al-Zabin
    • 1
  • Heba Bargouthi
    • 1
  • Iman Maharmeh
    • 1
  1. 1.Computer Engineering Department, Faculty of Engineering TechnologyAl-Balqa‘ Applied UniversityAmmanJordan

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