An improved fitness function for automated cryptanalysis using genetic algorithm

Md. Shafiul Alam Forhad (Chittagong University of Engineering Technology)
Md. Sabir Hossain (Chittagong University of Engineering Technology)
Mohammad Obaidur Rahman (Chittagong University of Engineering Technology)
Md. Mostafizur Rahaman (Chittagong University of Engineering Technology)
Md. Mokammel Haque (Chittagong University of Engineering Technology)
Md. Kamrul Hossain (Chittagong University of Engineering Technology)

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

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.