Journal of Computer Sciences and Applications
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Journal of Computer Sciences and Applications. 2015, 3(2), 52-55
DOI: 10.12691/jcsa-3-2-6
Open AccessResearch Article

Cryptanalysis Using Soft Computing Techniques

Harsh Bhasin1, and Asif Hameed Khan1

1Department of Computer Sc.&Engg, Jamia Hamdard University, New Delhi-62, India

Pub. Date: April 16, 2015
(This article belongs to the Special Issue Applicability of Soft Computing in NP Hard Problems)

Cite this paper:
Harsh Bhasin and Asif Hameed Khan. Cryptanalysis Using Soft Computing Techniques. Journal of Computer Sciences and Applications. 2015; 3(2):52-55. doi: 10.12691/jcsa-3-2-6

Abstract

This paper proposes a Genetic Algorithm (GAs) based cryptanalysis technique. Genetic Algorithms are the optimization techniques which are also known for robustness. The analysis and the involved theory have been presented in the paper. The designing of fitness function has been done using the statistical analysis of a Standard English Language documents. The technique has been verified using 9 text documents of about 4000 words and the results are encouraging. The technique paves way of Soft Computing techniques in Cryptanalysis.

Keywords:
Cryptanalysis Cryptography Genetic Algorithms (GAs)

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  Delman, “Genetic Algorithm in Cryptography”. Rochester Institute of Technology, Rochester, New York, 2004.
 
[2]  Goldberg, “Genetic Algorithm in search, Optimisation and Machine learning”, Addison Wesley Longman, London, 2006.
 
[3]  Akpinor and Bayhan, “A Hybrid Genetic Algorithm for Mixed Model Assembly Line Balancing Problem with Parallel Workstation and Zoning Constraints”, Engineering Applications of Artificial Intelligence, Vol, 24, pp. 449-457,2011.
 
[4]  Al-Duwaish, “A Genetic Approach to the identification of Linear Dynamical Systems with Static Non-Linearities”, International Journal of system Science, Vol, 31, pp, 307-313, 2000.
 
[5]  Benjamin et al, “Genetic Algorithm using for a Batch Fermentation Process Identification”, Journal of Applied Science, Vol. 8, pp. 2272-2278, 2008.
 
[6]  Da Silva et al, “Genetic Algorithm with local search optimization for multiple sequences Alignment”, Applied Intelligence, Vol. 32, pp. 164-172, 2010.
 
[7]  Paplinski. “Genetic Algorithm with Simplex Crossover for Identification of Time Delays”, Intellegent Information System, pp. 337-346, 2010.
 
[8]  Roeva and Fidanova, “Chapter 13 A Comparison of Genetic Algorithm and Ant Colony optimization for modelling of E. Coli Cultivation Process”, Real-world application op Genetic Algorithm, In Tech, pp-261-282, 2012.
 
[9]  Roeva and Slavov, “Fed-batch cultivation control based on Genetic Algorithm PID controlled Tuning”. Lecture notes on computer science, Springer-Verlag Berlin Heidelberg, Vol. 6046, pp. 289-296, 2011.
 
[10]  Eiben Et al, “Parameter Control in Evolutionary Algorithm”, IEEE Transactions on Evolutionary Computation, vol. 3, 1999.
 
[11]  Nowotnaik and Kucharski, “ GPU-based tuning of Quantum-Inspired Genetic Algorithm for a combinatorial optimization problem”, Bulletin of the polish Academy of Science, Technical Sciences, Vol. 60, pp. 373-330, 2012.
 
[12]  Saremi et al, “ Tuning the Parameters of a Genetic Algorithm to solve vehicle routing Problem with Backhauls using Design of Experiments”, International Journal of Operations Research, Vol. 4, pp. 206-219, 2007.
 
[13]  Fidanova, “Simulated Annealing: A Monte Carlo method for GPS surveying”, Computational Science-2006, Lecture notes in computer science No. 3991, pp. 1009-1012, 2006.
 
[14]  Mitchell and Melanie, “An introduction to a Genetic Algorithm”, MIT press paperback edition, 1996.
 
[15]  Holland and John, “Adaptation in natural and artificial systems”, A Brad Ford Book, 1992.
 
[16]  Alander, “On optimal population size of genetic algorithm”, In Proceedings of the IEEE computer systems and software engineering, pp. 65-69, 1992.
 
[17]  Diaz-Gomaz and Hougen, “Initial population for genetic algorithms: A metrics approach”, In proceedings of 2007 International conference of Genetic and Evolutionary Methods, CSREA Press, pp. 43-49, 2007.
 
[18]  Piszcz and Soule, “Genetic Programming: optimal population sizes for varying complexity problems”, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 953-954, 2006.
 
[19]  Koumousis and Katsaras, “Asaw tooth Genetic Algorithm combining the effects of variable population size and re-initialization to enhance performance”, IEEE Transaction on evolutionary computation, vol. 10, pp. 19-28, 2006.
 
[20]  Goldberg et al, “Bayesuan Optimization Algorithm, population sizing and time to convergence”, Illinois genetic Algorithms laboratory, University of Illinois, USA, 2000.
 
[21]  Lobo and Goldberg, “The parameter less genetic algorithm in practice”, Information Science, Informatics and computer science, Vol, 167, pp. 217-232, 2004.
 
[22]  Lobo and Lima, “A review of adaptive population sizing schemes in Genetic Algorithms”, In proceedings of the Genetic and Evolutionary Computation conference, pp. 228-234, 2005.
 
[23]  Spillmanet al, “Use of Genetic Algorithm in the cryptanalysis of simple substitution ciphers”, Crypto logia, Vol. 17, pp. 31-44, 1993.
 
[24]  Matthews and R.A.J, “The use of Genetic algorithm in cryptanalysis”, Cryptologia, Vol. 17, pp. 187-201, 1993.
 
[25]  Spillman, “Cryptanalysis of Knapsack Cipher using Genetic Algorithms”, Cryptologia, Vol. 17, pp. 367-377, 1993.
 
[26]  Clark, “Modern optimization algorithm for cryptanalysis”, In proceedings of the 1994 second Australian and New Zealand Conference on Intelligent Information system, pp. 258-262, 1994.
 
[27]  Lin et al, “A genetic algorithm for cipher text- only attack in cryptanalysis”, In IEEE International Conference on systems, Man and Cybernetics, Vol. 1, pp. 650-654, 1995.
 
[28]  Clark et al, “Combinatorial Optimization and the Knapsack cipher”, Cryptologia, Vol 20, pp. 85-93, 1996.
 
[29]  Clark et al, “Cryptanalysis of polyalphabetic substitution Ciphers using a parallel Genetic Algorithm”, In proceedings of IEEE International Symposium on Information and its applications, 1996.
 
[30]  Clark and Dawson, “A Parallel Genetic Algorithm for Cryptanalysis of Polyalphabetic Substitution Cipher”, Cryptologia, Vol. 21, pp. 129-138, 1997.
 
[31]  Kolodziejczyk et al, “The application of genetic algorithm in cryptanalysis of Knapsack Cipher”, In Proceeding of Fourth International Conference PRIP’97 pattern recognition and information processing, pp. 394-401, 1997.
 
[32]  Clark and Dawson, “Optimization Heuristics for the automated cryptanalysis of Classical Ciphers”, Journal of Combinatorial Mathematics and combinatorial computing, Vol. 28, pp. 63-86, 1998.
 
[33]  Yaseenaqnd Sahasrabuddhe, “A Genetic Algorithm for the cryptanalysis of chorrivest Knapsack public key cryptosystem (PKC)”, In proceedings of third international conference on Computational Intelligence and Multimedia Applications, pp. 81-85, 1999.
 
[34]  Grundlingh and Van Vuuren, “Using genetic algorithm to break a simple cryptographic Cipher”, Retrieved from http://dip.sun.ac.za/nvuuren/abstracts/abstr-genetic,htm, 2003.