Exploring Chaotic Neural Network for Cryptographic Hash Function
Due to the one way property of neural networks and high sensitivity of chaotic systems, chaotic neural networks make an ideal candidate for cryptographic hash function design. In this paper, a novel algorithm is proposed to construct an efficient cryptographic hash function using a four layer chaotic neural network. The proposed hash function satisfies the security requirements of confusion and diffusion, and the mechanism allows flexibility of the hash value length, which makes it resistant to birthday attack for hash lengths longer than 128 bits. Moreover, the running time of a neural network can be reduced with the help of parallel processing. The statistical analysis of the proposed algorithm proves it to be a promising choice for cryptographic hash function design.
KeywordsChaotic neural network Hash function Security Chaotic systems
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