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Differential Cryptanalysis of Symmetric Block Ciphers Using Memetic Algorithms

  • Kamil DworakEmail author
  • Urszula Boryczka
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11432)

Abstract

The paper presents a new differential cryptanalysis attack based on memetic algorithms. A prepared attack is directed against the ciphertext generated by one of the most popular ciphers named Data Encryption Standard (DES) reduced to six rounds of an encryption algorithm. The main purpose of the proposed MASA attack is to indicate the last encryption subkey, which allows the cryptanalyst to find 48 from 56 bits of decrypting key. With a simple comprehensive search, it’s possible to get the remaining 8 bits. The memetic attack is based on the simulated annealing algorithm, used to improve the local search process, to achieve the best possible solution. The described algorithm will be compared with a genetic algorithm attack, named NGA, based on an additional heuristic operator.

Keywords

Differential cryptanalysis Memetic algorithms DES Cryptography Simulated annealing 

References

  1. 1.
    Schneier, B.: Applied Cryptography: Protocols, Algorithms, and Source Code in C. Wiley, New York (1996)zbMATHGoogle Scholar
  2. 2.
    Menezes, A.J., Oorschot, P.C., Vanstone, S.A.: Handbook of Applied Cryptography. CRC Press, Boca Raton (1997)zbMATHGoogle Scholar
  3. 3.
    Biham, E., Shamir, A.: Differential cryptanalysis of DES-like cryptosystems. J. Cryptol. 4(1), 3–72 (1991)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Pieprzyk, J., Hardjono, T., Seberry, J.: Fundamentals of Computer Security. CRC Press, Boca Raton (2003)CrossRefGoogle Scholar
  5. 5.
    Song, J., Zhang, H., Meng, Q., Zhangyi, W.: Cryptanalysis of four-round DES based on genetic algorithm. In: Wireless Communications, Networking and Mobile Computing, pp. 2326–2329. IEEE (2007)Google Scholar
  6. 6.
    Tadros, T., Hegazy, A., Badr, A.: Genetic algorithm for DES cryptanalysis. Int. J. Comput. Sci. Netw. Secur. 10(5), 5–11 (2007)Google Scholar
  7. 7.
    Dworak, K., Boryczka, U.: Genetic algorithm as optimization tool for differential cryptanalysis of DES6. In: Nguyen, N.T., Papadopoulos, G.A., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds.) ICCCI 2017. LNCS (LNAI), vol. 10449, pp. 107–116. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-67077-5_11CrossRefGoogle Scholar
  8. 8.
    Dworak, K., Boryczka, U.: Differential cryptanalysis of FEAL4 using evolutionary algorithm. In: Nguyen, N.-T., Manolopoulos, Y., Iliadis, L., Trawiński, B. (eds.) ICCCI 2016. LNCS (LNAI), vol. 9876, pp. 102–112. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-45246-3_10CrossRefGoogle Scholar
  9. 9.
    Dworak, K., Nalepa, J., Boryczka, U., Kawulok, M.: Cryptanalysis of SDES using genetic and Memetic algorithms. In: Król, D., Madeyski, L., Nguyen, N.T. (eds.) Recent Developments in Intelligent Information and Database Systems. SCI, vol. 642, pp. 3–14. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-31277-4_1CrossRefGoogle Scholar
  10. 10.
    Garg, P.: A comparison between Memetic algorithm and genetic algorithm for the cryptanalysis of simplified data encryption standard algorithm. Int. J. Netw. Secur. Appl. (IJNSA) 1(1), 34–42 (2009)Google Scholar
  11. 11.
    Jain, A., Chaudhari, N.S.: A new heuristic based on the cuckoo search for cryptanalysis of substitution ciphers. In: Arik, S., Huang, T., Lai, W.K., Liu, Q. (eds.) ICONIP 2015. LNCS, vol. 9490, pp. 206–215. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-26535-3_24CrossRefGoogle Scholar
  12. 12.
    Jain, A., Chaudhari, N.S.: A novel cuckoo search strategy for automated cryptanalysis: a case study on the reduced complex knapsack cryptosystem. Int. J. Syst. Assur. Eng. Manag. 9(4), 942–961 (2017)CrossRefGoogle Scholar
  13. 13.
    Abd-Elmonim, W.G., Ghali, N.I., Hassanien, A.E., Abraham, A.: Known-plaintext attack of des-16 using particle swarm optimization. In: Third IEEE World Congress on Nature and Biologically Inspired Computing, pp. 12–16 (2011)Google Scholar
  14. 14.
    Stallings, W.: Cryptography and Network Security: Principles and Practice. Pearson, Upper Saddle River (2011)Google Scholar
  15. 15.
    Stinson, D.R.: Cryptography: Theory and Practice. CRC Press, Boca Raton (1995)zbMATHGoogle Scholar
  16. 16.
    Moscato, P.: On evolution, search, optimization, genetic algorithms and martial arts: towards Memetic algorithms. In: Caltech Concurrent Computation Program (1989)Google Scholar
  17. 17.
    Neri, F., Cotta, C., Moscato, P.: Handbook of Memetic Algorithms, Studies in Computational Intelligence, vol. 379. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-23247-3CrossRefGoogle Scholar
  18. 18.
    Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer, London (1996).  https://doi.org/10.1007/978-3-662-03315-9CrossRefzbMATHGoogle Scholar
  19. 19.
    Stamp, M., Low, R.M.: Applied Cryptanalysis. Breaking Ciphers in the Real World. Wiley-Interscience, Hoboken (2007)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of SilesiaSosnowiecPoland
  2. 2.Future ProcessingGliwicePoland

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