Hash function based on efficient Chaotic Neural Network

Abstract

This paper presents an efficient algorithm for constructing a secure Hash function based on Chaotic Neural Network structure. The proposed Hash function includes two main operations: Generation of Neural Network parameters using fast and efficient Chaotic Generator and Iteration of the message through the Chaotic Neural Network. Our theoretical analysis and experimental simulations showed that the implemented Hash function has good statistical properties, strong Collision Resistance and High Message Sensitivity.