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基于DTMP和快速学习规则的神经密码算法 被引量:2

Neural cryptography algorithm based on "Do not Trust My Partner" and fast learning rule
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摘要 针对神经密码中如何以较短的同步时间获得较高的安全性这一密钥交换问题,提出了一种基于"不要相信我的伙伴"(DTMP)和快速学习规则的联合算法。该算法可以通过在公共信道上以一定的概率发送错误比特来干扰攻击者对交互信息的窃听,以达到降低被动攻击成功率的目的,同时通过估计通信双方神经网络输出不相等的概率来判断通信双方的同步程度;然后根据通信双方的同步程度来确定权值的修改幅度,从而加快同步进程。仿真实验表明,联合算法所需同步时间比原DTMP算法少,且当通信双方不同时发送错误信息时,联合算法的安全性略高于DTMP原算法;而与反馈算法相比,联合算法在同步时间和安全性方面优势明显。实验结果表明联合算法能以较短的同步时间获得较高的安全性。 Focusing on the key exchange problem of how to get the higher security for neural cryptography in the short time of the synchronization, a new hybrid algorithm combining the features of "Do not Trust My Partner" (DTMP) and the fast learning rule was proposed. The algorithm could send erroneous output bits in the public channel to disrupt the attacker's eavesdropping of the exchanged bits and reduce the success rate of passive attack. Meanwhile, the proposed algorithm estimated the synchronization by estimating the probability of unequal outputs, then adjusted the change of weights according to the level of synchronization to speed up the process of synchronization. The simulation results show that the proposed algorithm outperforms the original DTMP in the time needed for the partners to synchronize. Moreover, the proposed algorithm is securer than the original DTMP when the partners do not send erroneous output bits at the same time. And the proposed algorithm outperforms the feedback algorithm in both the synchronization time and security obviously. The experimental results show that the proposed algorithm can obtain the key with a high level of security and a less synchronization time.
出处 《计算机应用》 CSCD 北大核心 2015年第6期1683-1687,共5页 journal of Computer Applications
基金 重庆市自然科学基金资助项目(ctsc2014cyj A40053) 重庆市教委科学技术研究项目(KJ130519)
关键词 树型奇偶机 不要相信我的伙伴 学习规则 几何攻击 简单攻击 Tree Parity Machine (TPM) Do not Trust My Partner (DTMP) learning rule geometric attack simple attack
作者简介 作者简介:张力生(1965-),男,四川宜宾人,教授,硕士,CCF会员,主要研究方向:数据挖掘、神经网络 刘凤钗(1988-),女,河北石家庄人,硕士研究生,主要研究方向:神经密码学 董滔(1981-),男,重庆人,副教授,博士,主要研究方向:神经网络 通信作者电子邮箱zhanghc@cqupt.edu.cn,张化川(1979-),男,四川大竹人,讲师,硕士,CCF会员,主要研究方向:数据挖掘、神经网络 胡文婕(1981-),女,重庆人,讲师,博士,主要研究方向:复杂网络。
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参考文献13

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