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Utilizing Ant Colony Optimization to Construct an S-Box Based on the 2D Logistic-Sine Coupled Map

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Applications of Ant Colony Optimization and its Variants

Part of the book series: Springer Tracts in Nature-Inspired Computing ((STNIC))

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Abstract

ACO is a combinatorial optimization method that draws inspiration from food searching, pheromone trails, and heuristic information employed by ants. The Substitution Box (S-Box) holds significant importance within symmetric key cryptography algorithms, notably in block ciphers. A secure S-Box requires high non-linearity, resistance to algebraic attacks, and diffusion of input changes to output changes. This study investigates the utilization of ACO for constructing an S-Box, employing the 2D Logistic-Sine Coupled Map (2D-LSCM) as the underlying framework. More precisely, a version of ACO for continuous optimization is used for optimizing the parameters of 2DLSCM. This chaotic map is used for an effective shuffling of an S-Box component and in the permutation of an image encryption. The analyses of results and security provide evidence that S-Box exhibits a high level of security suitable for an image encryption scheme.

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Author information

Authors and Affiliations

  1. Department of Natural and Mathematical Science, Tarsus University, Engineering Faculty, Mersin, 33400, Türkiye

    Serap Şahinkaya

  2. Department of Computer Engineering, Tarsus University, Engineering Faculty, Mersin, 33400, Türkiye

    Deniz Ustun

Authors
  1. Serap Şahinkaya
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  2. Deniz Ustun
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Correspondence to Deniz Ustun .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Techno International New Town, New Town, West Bengal, India

    Nilanjan Dey

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Şahinkaya, S., Ustun, D. (2024). Utilizing Ant Colony Optimization to Construct an S-Box Based on the 2D Logistic-Sine Coupled Map. In: Dey, N. (eds) Applications of Ant Colony Optimization and its Variants. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-99-7227-2_6

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