On the Cryptanalysis of a Simplified AES Using a Hybrid Binary Grey Wolf Optimization

Rizk M. Rizk-Allah, Hatem Abdulkader, Samah S. Abd Elatif, Diego Oliva (), Guillermo Sosa-Gómez and Václav Snášel
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Rizk M. Rizk-Allah: Department of Basic Engineering Science, Faculty of Engineering, Menoufia University, Shebin El-kom 32511, Menoufia, Egypt
Hatem Abdulkader: Department of Information Systems, Faculty of Computers and Information, Menoufia University, Shebin El-kom 32511, Menoufia, Egypt
Samah S. Abd Elatif: Department of Basic Engineering Science, Higher Institute of Engineering and Technology, Tanta 31739, Egypt
Diego Oliva: Departamento de Innovación Basada en la Información y el Conocimiento, Universidad de Guadalajara, CUCEI, Guadalajara 44430, Mexico
Guillermo Sosa-Gómez: Facultad de Ciencias Económicas y Empresariales, Universidad Panamericana, Álvaro del Portillo 49, Zapopan 45010, Mexico
Václav Snášel: Faculty of Electrical Engineering and Computer Science, VŠB-Technical University of Ostrava, 70800 Ostrava, Czech Republic

Mathematics, 2023, vol. 11, issue 18, 1-16

Abstract: Cryptosystem cryptanalysis is regarded as an NP-Hard task in modern cryptography. Due to block ciphers that are part of a modern cipher and have nonlinearity and low autocorrelation in their structure, traditional techniques and brute-force attacks suffer from breaking the key presented in traditional techniques, and brute-force attacks against modern cipher S-AES (simplified-advanced encryption standard) are complex. Thus, developing robust and reliable optimization with high searching capability is essential. Motivated by this, this paper attempts to present a novel binary hybridization algorithm based on the mathematical procedures of the grey wolf optimizer (GWO) and particle swarm optimization (PSO), named BPSOGWO, to deal with the cryptanalysis of (S-AES). The proposed BPSOGWO employs a known plaintext attack that requires only one pair of plaintext–ciphertext pairs instead of other strategies that require more pairs (i.e., it reduces the number of messages needed in an attack, and secret information such as plaintext-ciphertext pairs cannot be obtained easily). The comprehensive and statistical results indicate that the BPSOGWO is more accurate and provides superior results compared to other peers, where it improved the cryptanalysis accurateness of S-AES by 82.5%, 84.79%, and 79.6% compared to PSO, GA, and ACO, respectively. Furthermore, the proposed BPSOGWO retrieves the optimal key with a significant reduction in search space compared to a brute-force attack. Experiments show that combining the suggested fitness function with HPSOGWO resulted in a 109-fold reduction in the search space. In cryptanalysis, this is a significant factor. The results prove that BPSOGWO is a promising and effective alternative to attack the key employed in the S-AES cipher.

Keywords: cryptanalysis; simplified-AES; binary optimization; grey wolf optimizer; particle swarm optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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