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An Improved Genetic Algorithm and A New Discrete Cuckoo Algorithm for Solving the Classical Substitution Cipher

An Improved Genetic Algorithm and A New Discrete Cuckoo Algorithm for Solving the Classical Substitution Cipher

Ashish Jain, Narendra S. Chaudhari
Copyright: © 2021 |Pages: 25
ISBN13: 9781799880486|ISBN10: 1799880486|EISBN13: 9781799880998
DOI: 10.4018/978-1-7998-8048-6.ch067
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MLA

Jain, Ashish, and Narendra S. Chaudhari. "An Improved Genetic Algorithm and A New Discrete Cuckoo Algorithm for Solving the Classical Substitution Cipher." Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms, edited by Information Resources Management Association, IGI Global, 2021, pp. 1431-1455. https://doi.org/10.4018/978-1-7998-8048-6.ch067

APA

Jain, A. & Chaudhari, N. S. (2021). An Improved Genetic Algorithm and A New Discrete Cuckoo Algorithm for Solving the Classical Substitution Cipher. In I. Management Association (Ed.), Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms (pp. 1431-1455). IGI Global. https://doi.org/10.4018/978-1-7998-8048-6.ch067

Chicago

Jain, Ashish, and Narendra S. Chaudhari. "An Improved Genetic Algorithm and A New Discrete Cuckoo Algorithm for Solving the Classical Substitution Cipher." In Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms, edited by Information Resources Management Association, 1431-1455. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-8048-6.ch067

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Abstract

Searching secret key of classical ciphers in the keyspace is a challenging NP-complete problem that can be successfully solved using metaheuristic techniques. This article proposes two metaheuristic techniques: improved genetic algorithm (IGA) and a new discrete cuckoo search (CS) algorithm for solving a classical substitution cipher. The efficiency and effectiveness of the proposed techniques are compared to the existing tabu search (TS) and genetic algorithm (GA) techniques using three criteria: (a) average number of key elements correctly detected, (b) average number of keys examined before determining the required key, and (c) the mean performance time. As per the results obtained, the improved GA is comparatively better than the existing GA for criteria (a) and (c), while the proposed CS strategy is significantly better than rest of the algorithms (i.e., GA, IGA, and TS) for all three criteria. The obtained results indicate that the proposed CS technique can be an efficient and effective option for solving other similar NP-complete combinatorial problems also.

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