Cryptanalysis of Substitution Ciphers Using Scatter Search

  • Mohamed Amine Garici
  • Habiba Drias
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3562)

Abstract

This paper presents an approach for the automated cryptanalysis of substitution ciphers based on a recent evolutionary metaheuristic called Scatter Search. It is a population-based metaheuristic founded on a formulation proposed two decades ago by Fred Glover. It uses linear combinations on a population subsets to create new solutions while other evolutionary approaches like genetic algorithms resort to randomization. First, we implement the procedures of the scatter search for the cryptanalysis of substitution ciphers. This implementation can be used as a framework for solving permutation problems with scatter search. Then, we test the algorithm and show the importance of the improvement method and the contribution of subset types. Finally, we compare its performances with those of a genetic algorithm.

Keywords

automated cryptanalysis substitution ciphers scatter search evolutionary approach heuristic search genetic algorithm optimization problem 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Campos, V., Glover, F., Laguna, M., Martí, R.: An Experimental Evaluation of a Scatter Search for the Linear Ordering Problem. Journal of Global Optimization 21 (2001)Google Scholar
  2. 2.
    Clark, A.J.: Optimisation Heuristics for Cryptology. PhD Thesis, Queensland University of Technology (1998)Google Scholar
  3. 3.
    Clark, J.A.: Metaheuristic Search as a Cryptological Tool. PhD Thesis, University of York (2001)Google Scholar
  4. 4.
    Drias, H., Azi, N.: Scatter search for SAT and MAX-W-SAT problems. In: Ohio, U.S.A. (ed.) Proceedings of the IEEE SSST, Ohio, USA (2001)Google Scholar
  5. 5.
    Forsyth, W.S., Safavi-Naini, R.: Automated cryptanalysis of substitution ciphers. Cryptologia 4(17) (1991)Google Scholar
  6. 6.
    Glover, F.: Heuristics for Integer Programming Using Surrogate Constraints. Decision Sciences 8(1) (1977)Google Scholar
  7. 7.
    Glover, F., Kelly, J.P., Laguna, M.: Genetic Algorithms and Taboo Search: Hybrids for Optimization. Computers and Operation Reseach 22(1) (1995)Google Scholar
  8. 8.
    Glover, F.: A Template for Scatter Search and Path Relinking. Notes in Computer Sciences. Springer, Heidelberg (1998)Google Scholar
  9. 9.
    Laguna, M., Armentano, V.: Lessons from Applying and Experimenting with Scatter Search. In: Rego, C., Alidaee, B. (eds.) Adaptive Memory and Evolution: Tabu Search and Scatter Search (2003)Google Scholar
  10. 10.
    Russell, M., Clark, J.A., Stepney, S.: Using Ants to Attack a Classical Cipher. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003. LNCS, vol. 2723, Springer, Heidelberg (2003)CrossRefGoogle Scholar
  11. 11.
    Spillman, R., Janssen, M., Nelson, B., Kepner, M.: Use of a genetic algorithm in the cryptanalysis of simple substitution ciphers. Cryptologia 17(1) (1993)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Mohamed Amine Garici
    • 1
  • Habiba Drias
    • 2
  1. 1.Electronics and Computer Science Faculty, Research Laboratory in Artificial IntelligenceLRIA-USTHBAlgiersAlgeria
  2. 2.Computer Science National Institute I.N.I.AlgiersAlgeria

Personalised recommendations