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Abstract
This paper proposes an advanced encryption standard (AES) cryptosystem based on memristive neural network. A memristive chaotic neural network is constructed by using the nonlinear characteristics of a memristor. A chaotic sequence, which is sensitive to initial values and has good random characteristics, is used as the initial key of AES grouping to realize "one-time-one-secret" dynamic encryption. In addition, the Rivest-Shamir-Adleman (RSA) algorithm is applied to encrypt the initial values of the parameters of the memristive neural network. The results show that the proposed algorithm has higher security, a larger key space and stronger robustness than conventional AES. The proposed algorithm can effectively resist initial key-fixed and exhaustive attacks. Furthermore, the impact of device variability on the memristive neural network is analyzed, and a circuit architecture is proposed.
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Details
1 University of Electronic Science and Technology of China, State Key Laboratory of Electronic Thin Films and Integrated Devices, Chengdu, People’s Republic of China (GRID:grid.54549.39) (ISNI:0000 0004 0369 4060)
2 Beijing Microelectronics Technology Institute (BMTI), Beijing, People’s Republic of China (GRID:grid.495597.3) (ISNI:0000 0004 8343 3310)
3 Nanyang Technological University, Singapore, Singapore (GRID:grid.59025.3b) (ISNI:0000 0001 2224 0361)