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Best Fit DNA-Based Cryptographic Keys: The Genetic Algorithm Approach.
Mukherjee, Pratyusa; Garg, Hitendra; Pradhan, Chittaranjan; Ghosh, Soumik; Chowdhury, Subrata; Srivastava, Gautam.
Afiliación
  • Mukherjee P; School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, Bhubaneshwar 751024, India.
  • Garg H; Department of Computer Engineering and Applications, GLA University, Mathura 281406, India.
  • Pradhan C; School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, Bhubaneshwar 751024, India.
  • Ghosh S; Siemens Technology Services Private Limited, Mumbai 560100, India.
  • Chowdhury S; Sri Venkateswara College of Engineering Technology, Chittoor 517127, India.
  • Srivastava G; Department of Mathematics and Computer Science, Brandon University, Brandon, MB R7A 6A9, Canada.
Sensors (Basel) ; 22(19)2022 Sep 27.
Article en En | MEDLINE | ID: mdl-36236428
ABSTRACT
DNA (Deoxyribonucleic Acid) Cryptography has revolutionized information security by combining rigorous biological and mathematical concepts to encode original information in terms of a DNA sequence. Such schemes are crucially dependent on corresponding DNA-based cryptographic keys. However, owing to the redundancy or observable patterns, some of the keys are rendered weak as they are prone to intrusions. This paper proposes a Genetic Algorithm inspired method to strengthen weak keys obtained from Random DNA-based Key Generators instead of completely discarding them. Fitness functions and the application of genetic operators have been chosen and modified to suit DNA cryptography fundamentals in contrast to fitness functions for traditional cryptographic schemes. The crossover and mutation rates are reducing with each new population as more keys are passing fitness tests and need not be strengthened. Moreover, with the increasing size of the initial key population, the key space is getting highly exhaustive and less prone to Brute Force attacks. The paper demonstrates that out of an initial 25 × 25 population of DNA Keys, 14 keys are rendered weak. Complete results and calculations of how each weak key can be strengthened by generating 4 new populations are illustrated. The analysis of the proposed scheme for different initial populations shows that a maximum of 8 new populations has to be generated to strengthen all 500 weak keys of a 500 × 500 initial population.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proyectos de Investigación / Algoritmos Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article País de afiliación: India Pais de publicación: CH / SUIZA / SUÍÇA / SWITZERLAND

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proyectos de Investigación / Algoritmos Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article País de afiliación: India Pais de publicación: CH / SUIZA / SUÍÇA / SWITZERLAND