Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/123456789/30352
Title: Generating highly nonlinear S-boxes using a hybrid approach with particle swarm optimization
Authors: Lapina, M. A.
Лапина, М. А.
Babenko, M. G.
Бабенко, М. Г.
Keywords: S-box;Particle swarm optimization;Random Key
Issue Date: 2024
Publisher: IGI Global
Citation: Shadab M., Javed M.D.S., Sajid M., Prasad M., Lapina M.A., Babenko M. Generating highly nonlinear S-boxes using a hybrid approach with particle swarm optimization // Nature-Inspired Optimization Algorithms for Cyber-Physical Systems. - 2024. - pp. 1 - 29. - DOI: 10.4018/979-8-3693-6834-3.ch001
Series/Report no.: Nature-Inspired Optimization Algorithms for Cyber-Physical Systems
Abstract: A substitution box (S-box) is a fundamental component in cryptographic algorithms that enhance data security by providing a complex mapping between input and output values. S-box strengthens the encryption and decryption process by introducing nonlinearity and protecting the encrypted data against various differential and linear cryptanalytic attacks. The problem of generating an S-box with optimal properties is challenging and falls under the category of NP-Hard problems. This study proposes a hybrid approach combining the Particle Swarm optimization algorithm (PSO) and the Booster algorithm to construct a highly nonlinear S-box with low computational efforts. The PSO algorithm, assisted by the Transfer function and Random Key (RK), is utilized to navigate the large permutation search space to find an S-box with acceptable cryptographic properties. The Booster algorithm works based on random applications of local operators for shuffling the elements of the S-box with each other and transforming the elements' arrangement, resulting in a modified S-box with increased nonlinearity.
URI: https://dspace.ncfu.ru/handle/123456789/30352
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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