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中国物理学会期刊

基于混沌神经网络的单向Hash函数

CSTR: 32037.14.aps.55.5688

One-way Hash function based on chaotic neural network

CSTR: 32037.14.aps.55.5688
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  • 提出了一种基于混沌神经网络的单向Hash函数,该方法通过使用以混沌分段线性函数作为输出函数的神经网络和基于时空混沌的密钥生成函数实现明文和密钥信息的混淆和扩散,并基于密码块连接模式实现对任意长度的明文序列产生128位的Hash值.理论分析和实验结果表明,提出的Hash函数可满足所要求的单向性,初值和密钥敏感性,抗碰撞性和实时性等要求.

     

    In this paper, a new one-way Hash function is proposed based on chaotic neural network. With the neural network with piecewise linear chaotic map as the output function, the key generation function based on spatiotemporal chaotic system are used to realized the data confusion and diffusion. By the cipher block chaining mode, the proposed method can produce 128-bit Hash value for plaintext with arbitrary length. Theoretical analysis and experimental results indicate that the proposed Hash function satisfies the demands in performance, such as being one-way, having initial value and key sensitivity, collision resistance and real-time applicability.

     

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