一种基于神经网络的Hash函数算法研究

A Novel Hash Function Algorithm Based on the Neural Network

如何设计高效、安全的带秘密密钥的单向函数一直是现代密码学研究中的一个热点。首先用神经网络来训练一维非线性分段映射产生混沌序列,并利用该模型产生的非线性序列构造带秘密密钥的Hash函数,该算法的优点之一是神经网络隐式混沌映射关系使直接获取映射关系变得困难,实验结果表明,这种算法具有对初值有高度敏感性、很好的单向性、弱碰撞性,较基于单一混沌映射的Hash函数具有更强的保密性能,且实现简单。

How to design an efficient and secure keyed Hash function is always the hot point in modem cryptography researches.In this paper,A better chaos sequence is generated by the neural network through training the known chaotic sequence generated by a piecewise nonlinear,Then the sequence is used to construct keyed Hash function.One advantage of the algorithm is that the hidden-mapping model of neural network makes it difficult to get the direct mapping function of the ordinary chaos encryption algorithm.Simulation results show that the keyed Hash function based on the neural network has good one-way,weak collision property,better security and it can be realized easily.