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Multiple S-Box Correlation Energy Analysis Model Based on Particle Swarm Optimization

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 927))

Abstract

Aiming at the problem that the amount of calculation of correlation energy analysis is too large in the process of attacking multiple S-box corresponding keys, this paper proposes a multiple S-box correlation energy analysis model based on particle swarm optimization. The particle swarm optimization algorithm has the characteristics of simple structure, fast search speed and memory, therefore, our model simultaneously attacks multiple S-boxes, which can reduce the amount of calculation, thereby achieving the goal of recovering the key efficiently and correctly. Finally, experimental analysis and verification results of the DES algorithm indicate that our new energy analysis model has about 55% improvement in efficiency and 30% improvement in accuracy over traditional energy analysis models.

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Correspondence to Wu-jun Yao .

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Yao, Wj., Yang, Hb., Chen, L., Wei, B. (2019). Multiple S-Box Correlation Energy Analysis Model Based on Particle Swarm Optimization. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2019. Advances in Intelligent Systems and Computing, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-15035-8_38

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