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Neural Computing and Applications
Published in: Neural Computing and Applications 11/2019

28-05-2018 | Original Article

A novel efficient substitution-box design based on firefly algorithm and discrete chaotic map

Authors: Hussam A. Ahmed, Mohamad Fadli Zolkipli, Musheer Ahmad

Published in: Neural Computing and Applications | Issue 11/2019

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Abstract

Substitution boxes are essential nonlinear components responsible to impart strong confusion and security in most of modern symmetric ciphers. Constructing efficient S-boxes has been a prominent topic of interest for security experts. With an aim to construct cryptographically efficient S-box, a novel scheme based on firefly (FA) optimization and chaotic map is proposed in this paper. The anticipated approach generates initial S-box using chaotic map. The meta-heuristic FA is applied to find notable configuration of S-box that satisfies the criterions by guided search for near-optimal features by minimizing fitness function. The performance of proposed approach is assessed through well-established criterions such as bijectivity, nonlinearity, strict avalanche criteria, bit independence criteria, differential uniformity, and linear approximation probability. The obtained experimental results are compared with some recently investigated S-boxes to demonstrate that the proposed scheme has better proficiency of constructing efficient S-boxes.
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Metadata
Title
A novel efficient substitution-box design based on firefly algorithm and discrete chaotic map
Authors
Hussam A. Ahmed
Mohamad Fadli Zolkipli
Musheer Ahmad
Publication date
28-05-2018
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 11/2019
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3557-3

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