混沌映射和神经网络互扰的新型复合流密码  

New hybrid stream cipher based on chaos and neural networks

作　　者：陈铁明[1] 蒋融融[2] 

机构地区：[1]浙江工业大学计算机科学与技术学院,杭州310023 [2]浙江广播电视大学信息与工程学院,杭州310013

出　　处：《物理学报》2013年第4期22-28,共7页Acta Physica Sinica

基　　金：国家重点基础研究发展计划(批准号:2010CB328106-3);国家自然科学基金(批准号:61103044);国家高技术研究发展计划(批准号:2009AA043303);浙江省自然科学基金(批准号:Y1110567);浙江省科技计划(批准号:2010C31126;2011C21046);软件开发环境国家重点实验室(批准号:SKLSDE-2011KF-07)资助的课题~~

摘　　要：提出了一种将新型的神经网络互学习模型和常见的多混沌系统融合互扰的复合流密码方案.首先利用三个Logistics混沌映射产生的随机序列作为神经网络互学习模型中三个隐含层神经元的随机输入,神经网络交互学习达到内部权值同步后,再将同步权值映射为随机序列并与三个Logistics序列复合产生最终的密钥流.实验表明,产生的密钥流具有更好的随机性,混沌流加密应用效果好.A hybrid stream cipher scheme is proposed based on the novel interacting neural networks and the multiple chaotic systems. At first, random sequences generated by 3 independent logistics functions respectively are taken as dynamic inputs to 3 hidden layers of the interacting neural networks model. Then two inner weights of the two structures of neural networks will be synchronized through some steps of interacting learning, and the random key stream can be finally identified by combining the random sequence extracted from the aforementioned synchronized weight and 3 Logistics sequences. The comparison shows that the generated key stream performs the better randomness than others. As a good example, the proposed novel chaos-based stream cipher works perfectly on digital image encryption.

关 键 词：混沌映射 神经网络 权值同步 随机密钥流 

分 类 号：TN918.1[电子电信—通信与信息系统]