一种新的基于神经网络混沌吸引子的公钥密码算法  

A New Pub lic-key Cryp tography Based on Chaotic Attractors of Neural Networks

作　　者：刘年生[1] 郭东辉[2] 

机构地区：[1]集美大学计算机工程学院,福建厦门361021 [2]厦门大学物理与机电工程学院,福建厦门361005

出　　处：《集美大学学报（自然科学版）》2005年第2期125-133,共9页Journal of Jimei University：Natural Science

基　　金：国家自然科学基金项目(69886002;60076015);福建省自然科学基金项目(A0010019)

摘　　要：论述了一种新的基于神经网络混沌吸引子的公钥密码算法,在过饱和贮存的Hopfield神经网络模型中混沌吸引子与初始状态之间存在一种单向函数关系,改变神经网络的联结权矩阵,混沌吸引子及其相应的吸引域会随之发生改变,如果以联结权矩阵为陷门,并利用可交换的随机变换矩阵来改变神经网络的联结权矩阵,则可以创建一种新的Diffie-Hellman公钥加密算法.将随机变换矩阵作为私钥,而将变换后的神经网络联结突触矩阵作为公钥,介绍了这种新的公钥加密方案,并分析和讨论其安全性和加密效率.A new public-key cryptography based on chaotic attractors of neural networks is described. There is a one-way function between chaotic attractors and initial states in an Overstoraged Hopfield Neural Networks (OHNN), and each attractor and its correspond ing domain of attraction are changed with permuta- tion operations on the neural synaptic matrix. If the neural synaptic matrix is used as a trap door and changed by commutative random permutation matrix, a new cryptography technique accord ing to D iffie-Hellman public- key cryptosystem is proposed. By keeping the random permutation operation of the neural synaptic matrix as the secret key, and the neural synaptic matrix after permutation as public-key, a new encryption scheme for a public-key cryptosystem is introduced. Security of the new scheme is d iscussed.

关 键 词：神经网络 公钥密码体制 混沌吸引子 矩阵分解 

分 类 号：TP309.02[自动化与计算机技术—计算机系统结构]