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2017 | OriginalPaper | Chapter

Comparison of Effectiveness of Multi-objective Genetic Algorithms in Optimization of Invertible S-Boxes

Authors : Tomasz Kapuściński, Robert K. Nowicki, Christian Napoli

Published in: Artificial Intelligence and Soft Computing

Publisher: Springer International Publishing

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Abstract

Strength of modern ciphers depends largely on cryptographic properties of substitution boxes, such as nonlinearity and transparency order. It is difficult to optimize all such properties because they often contradict each other. In this paper we compare two of the most popular multi-objective genetic algorithms, NSGA-II and its steady-state version, in solving the problem of optimizing invertible substitution boxes. In our research we defined objectives as cryptographic properties and observed how they change within population during experiments.

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Title: Comparison of Effectiveness of Multi-objective Genetic Algorithms in Optimization of Invertible S-Boxes
Authors: Tomasz Kapuściński
Robert K. Nowicki
Christian Napoli
Publisher: Springer International Publishing
Book: Artificial Intelligence and Soft Computing
Print ISBN: 978-3-319-59059-2

Electronic ISBN: 978-3-319-59060-8

Copyright Year: 2017
DOI: https://doi.org/10.1007/978-3-319-59060-8_42

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