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A survey on the Metaheuristics for Cryptanalysis of Substitution and Transposition Ciphers

Arkan Kh Shakr Sabonchi*, Bahriye Akay

Computer Engineering Department, Erciyes University, Kayseri, 38039, Melikgazi, Turkey

* Corresponding Author:Arkan Kh Shakr Sabonchi. Email: email

Computer Systems Science and Engineering 2021, 39(1), 87-106. https://doi.org/10.32604/csse.2021.05365

Abstract

This paper presents state-of-art cryptanalysis studies on attacks of the substitution and transposition ciphers using various metaheuristic algorithms. Traditional cryptanalysis methods employ an exhaustive search, which is computationally expensive. Therefore, metaheuristics have attracted the interest of researchers in the cryptanalysis field. Metaheuristic algorithms are known for improving the search for the optimum solution and include Genetic Algorithm, Simulated Annealing, Tabu Search, Particle Swarm Optimization, Differential Evolution, Ant Colony, the Artificial Bee Colony, Cuckoo Search, and Firefly algorithms. The most important part of these various applications is deciding the fitness function to guide the search. This review presents how these algorithms have been implemented for cryptanalysis purposes. The paper highlights the results and findings of the studies and determines the gaps in the literature.

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APA Style
Sabonchi, A.K.S., Akay, B. (2021). A survey on the metaheuristics for cryptanalysis of substitution and transposition ciphers. Computer Systems Science and Engineering, 39(1), 87-106. https://doi.org/10.32604/csse.2021.05365
Vancouver Style
Sabonchi AKS, Akay B. A survey on the metaheuristics for cryptanalysis of substitution and transposition ciphers. Comput Syst Sci Eng. 2021;39(1):87-106 https://doi.org/10.32604/csse.2021.05365
IEEE Style
A.K.S. Sabonchi and B. Akay, “A survey on the Metaheuristics for Cryptanalysis of Substitution and Transposition Ciphers,” Comput. Syst. Sci. Eng., vol. 39, no. 1, pp. 87-106, 2021. https://doi.org/10.32604/csse.2021.05365



cc Copyright © 2021 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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