Memristor Based Chaotic Neural Network with Application in Nonlinear Cryptosystem
The global shift towards digitization has resulted in intensive research on Cryptographic techniques. Chaotic neural networks, augment the process of cryptography by providing increased security. In this paper, a description of an algorithm for the generation of an initial value for encryption using neural network involving memristor and chaotic polynomials is provided. The chaotic series that is obtained is combined with nonlinear 1 Dimensional and 2 Dimensional chaotic equations for the encryption process. A detailed analysis is performed to find the fastest converging neural network, complemented by the chaotic equations to produce least correlated ciphertext and plaintext. The use of Memristor in Neural Network as a generator for chaotic initial value as the encryption key and the involvement of nonlinear equations for encryption, makes the communication more confidential. The network can further be used for secure multi receiver systems.
KeywordsChaotic neural network Memristor Hermite polynomial Chebyshev polynomials 1 Dimensional chaotic maps 2 Dimensional chaotic maps
The authors would like to thank the faculty and staff of the Department of Electronics and Communication Engineering, SRM University for their support and guidance.
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