Multi-Objective Evolution of Strong S-Boxes Using Non-dominated Sorting Genetic Algorithm-II and Chaos for Secure Telemedicine

There exist several performance criteria for cryptographically strong substitution boxes which are often conflicting with each other. Constructing S-boxes that satisfy multiple criteria with optimal tradeoffs is one of the challenging tasks for cryptographers. In practice, the existing S-box designi...

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Bibliographic Details
Published in:IEEE access Vol. 10; p. 1
Main Authors: Ahmad, Musheer, Alkanhel, Reem, El-Shafai, Walid, Algarni, Abeer D., Abd El-Samie, Fathi E., Soliman, Naglaa F.
Format: Journal Article
Language:English
Published: Piscataway IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Autocorrelation functions
Boxes
Chaotic communication
Chaotic map
Cryptography
Design optimization
Encryption
Genetic algorithms
Medical imaging
Multi-Objective Evolution
Multiple criterion
Multiple objective analysis
Nonlinearity
NSGA-II
Optimization
Pareto optimization
Pareto optimum
Performance assessment
Permutations
Sociology
Sorting algorithms
Statistics
Substitution box
Telemedicine
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:There exist several performance criteria for cryptographically strong substitution boxes which are often conflicting with each other. Constructing S-boxes that satisfy multiple criteria with optimal tradeoffs is one of the challenging tasks for cryptographers. In practice, the existing S-box designing algorithms are used to optimize only a single performance criterion, mainly the nonlinearity, which usually resulted in weak scores of other equally significant criteria. To overcome this problem, a multi-objective optimization based method is presented in this paper which constructs 8×8 S-boxes satisfying multiple criteria of balancedness, high nonlinearity, low differential uniformity, and low auto-correlation. The fulfillment of multiple objectives is done by applying the chaos-assisted non-dominated sorting genetic algorithm-II to evolve S-boxes. The performance assessment of a proposed method and comparative analysis with available optimization based and other state-of-the art algorithms demonstrate its proficiency to generate significantly better S-box solutions with good Pareto-optimal security features. Eventually, the S-boxes with minimum NL of 110, DU as low as 8, and ACF as low as 80, are obtained after the optimization. Furthermore, the obtained Pareto-optimal S-box is utilized to put forward a medical image encryption algorithm for secure telemedicine services. The suggested encryption algorithm makes use of S-box for performing the required permutation and diffusion of images. The encryption performance assessment and comparison analyses validate its effectiveness for securing medical imagery data in telemedicine networks.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2022.3209202