A method for designing Hash function based on chaotic neural network
Bo He, Peng Lei, Pu Qin, Zhaolong Liu · Advances in intelligent systems research/Advances in Intelligent Systems Research · 2013
The neural network model has complex nonlinear behavior, which is very useful to design encryption algorithm and Hash function.In this paper, an algorithm for constructing one-way hash function based on chaotic neural network is proposed.The neural network model is initialized by two chaotic maps.Then, the message are divided into blocks with fixed length and inputted to neural network one by one.The final Hash value is extracted from status value of output layer cells.Theoretical analysis and computer simulation indicate that our algorithm has good statistical properties, strong collision resistance and high flexibility.It is practical and reliable, with high potential to provide data integrity.