Particle Swarm Optimization Based Highly Nonlinear Substitution-Boxes Generation for Security Applications

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Abstract

Symmetric encryption has been considered as one of the essential means of ensuring security of end to end communication. The robustness and strength of modern day block encryption systems are based on the cryptographic features of substitution-boxes which are used to inject confusion ability during substitution-phases. In this paper, as an alternative to random, chaos or algebraic based construction methods, we propose to present an efficient method for the generation of cryptographic highly nonlinear substitution-boxes. The nature-inspired particle swarm optimization is reconnoitered to develop proposed method wherein the initial population is generated through a simple but with rich dynamics chaotic Renyi map. The anticipated method is analyzed for different scenarios such as change in population size, number of iterations, and linear increase in inertial weight. The performance assessment of generated S-boxes under standard criterions corroborate that the proposed method has excellent cryptographic features and found grander than many recent optimization based S-box methods. Moreover, an image encryption application of proposed S-boxes is also suggested to determine their suitability and applicability for image based security applications.

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APA

Ahmad, M., Khaja, I. A., Baz, A., Alhakami, H., & Alhakami, W. (2020). Particle Swarm Optimization Based Highly Nonlinear Substitution-Boxes Generation for Security Applications. IEEE Access, 8, 116132–116147. https://doi.org/10.1109/ACCESS.2020.3004449

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