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Md. Shafiul Alam Forhad
Chittagong University of Engineering Technology

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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
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp643-648

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.
Co-Authors Md. Kamrul Hossain Md. Mokammel Haque Md. Mostafizur Rahaman Md. Sabir Hossain Mohammad Obaidur Rahman