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Effect of Variations in the Population Size and Generations of Genetic Algorithms in Cryptography - An Empirical Study

Affiliations

  • Department of Computer Science, Kristu Jayanti College, Bangalore – 560077, Karnataka, India
  • Department of Computer Science and Engineering, M. S. Engineering College, Bangalore – 562110, Karnataka, India

Abstract


Objectives: The implementation of Genetic algorithm in the symmetric block cipher Advanced Encryption Standard -128 (AES-128) algorithms to enhance the performance of cryptographic operations. Methods: Genetic algorithm is used for generating the best fit non-repetitive cipher key and for key distribution to design a dynamic Substitution box in AES-128. Findings: The study reveals that the efficiency of the cryptographic algorithm treated with Genetic algorithm is dependent on the variations in the number of generations and initial population size. The result shows that an optimum population size has less encryption and decryption time. Among the sample population size taken for the experiment, almost the average population size has minimum encryption and decryption time. Results from iteration variations shows that the average number of iterations has less encryption and decryption time. Improvements: The hybrid combination of Genetic algorithm and AES-128 can be further modified for images and audio messages also.

Keywords

Genetic Algorithm, Iterations, Non-Repetitive Cipher Key, Population Size, Substitution Box.

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