Probing the Genetic Algorithm Assisted Vigenère Cipher Cryptanalysis

The recent quest for automated decryption in different domains such as military, espionage, etc. has piqued the interest of the scientific community in developing computationally efficient frameworks for the same. In this regard, the current study demonstrates the successful application of a genetic...

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Bibliographic Details
Published in:2024 International Conference on Advances in Modern Age Technologies for Health and Engineering Science (AMATHE) pp. 1 - 6
Main Authors: V., Harshvardhan, Gupta, Kritesh Kumar, K.P., Soman
Format: Conference Proceeding
Language:English
Published: IEEE 16.05.2024
Subjects:
Buildings
Ciphers
Computer architecture
Distance measurement
fitness landscape
fixed key length
genetic algorithm
Military computing
Neural networks
Performance evaluation
Vigenère cipher
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Summary:The recent quest for automated decryption in different domains such as military, espionage, etc. has piqued the interest of the scientific community in developing computationally efficient frameworks for the same. In this regard, the current study demonstrates the successful application of a genetic algorithm (GA) for performing Vigenère cipher cryptanalysis under the constraint of a fixed key length. The presented framework conducts a comprehensive performance evaluation by investigating the convergence analysis of the GA under varying lengths of characters (with and without the use of an elitist selection method). Here, GA is utilized to search the prospective solution to the Vigenère cipher. Additionally, the evolution of the fitness landscape is analyzed across generations, providing a holistic understanding of the algorithm's effectiveness. The proposed computationally efficient approach enables us to understand the capabilities of GA in Vigenère cipher cryptanalysis. The scientific findings of this study will pave the way for the use of genetic algorithms indeciphering different cryptographic systems.
DOI:10.1109/AMATHE61652.2024.10582196