An improved fitness function for automated cryptanalysis using genetic algorithm

Md. Shafiul Alam Forhad, Md. Sabir Hossain, Mohammad Obaidur Rahman, Md. Mostafizur Rahaman, Md. Mokammel Haque, Md. Kamrul Hossain

Abstract


Genetic Algorithm (GA) is a popular desire for the researchers for creating an automated cryptanalysis system. GA strategy is useful for many problems. Genetic Algorithms try to solve problems by using genetic processes. Different techniques for deciding on fitness function relying on the ciphers have proposed by different researchers. The most necessary component is to set such a fitness function that can evaluate different types of ciphers on the identical scale. In this paper, we have proposed a combined fitness function that is valid for great sorts of ciphers. We use GA to select the fitness function. We have bought the higher result after imposing our proposed method.

Keywords


Cryptanalysis, Fitness function, Automated cryptanalysis, Genetic algorithm

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DOI: http://doi.org/10.11591/ijeecs.v13.i2.pp643-648

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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