强杂波环境下网络病毒传播灰阶菌群免疫算法

发布时间：2018-04-24 16:50

本文选题：网络病毒 + 免疫算法　；参考：《科技通报》2014年10期

【摘要】：网络病毒的入侵和传播通常伴随着强杂波信息的掩盖而提高其生存能力,研究一种有效的免疫算法是对抗病毒传播的关键。传统的抵御网络病毒传播的免疫方法采用人工免疫算法,该法基于熵权重属性分类时不能有效抵抗强杂波干扰的影响,抗病毒感染的免疫能力不高。本文提出一种基于自适应实时繁殖策略的灰阶菌群免疫算法,采用分段匹配白化滤波方法滤除杂波信息,构建强杂波环境下病毒传播数学演化模型,以信息熵作为病毒传播免疫分类属性,提出采用灰阶菌群聚类方法进行病毒特征免疫。进行仿真实验表明该算法能有效滤除病毒潜藏的杂波干扰,病毒信息特征菌群得到准确聚类,降低了计算机用户的感染率,实时性和稳定性好。
[Abstract]:The invasion and transmission of network viruses usually improve their survivability with the masking of strong clutter information. To study an effective immune algorithm is the key to fight the spread of virus. Artificial immune algorithm is used in the traditional immune method to resist the spread of network virus. This method can not effectively resist the influence of strong clutter when classifying based on entropy weight attribute, so the immune ability of anti-virus infection is not high. In this paper, a gray scale immune algorithm based on adaptive real-time propagation strategy is proposed. The segmented matched whitening filtering method is used to filter the clutter information, and the mathematical evolution model of virus propagation in strong clutter environment is constructed. The information entropy is used as the classification attribute of virus transmission immunity, and the gray scale bacteria cluster method is proposed to carry out the virus characteristic immunity. The simulation results show that the algorithm can effectively filter the clutter interference of virus, and the virus information characteristic bacteria can be clustered accurately, and the infection rate of computer users is reduced, and the real-time and stability are good.
【作者单位】：四川师范大学物理与电子工程学院;宜宾职业技术学院电子信息与控制工程系;宜宾职业技术学院人文社会科学系;
【分类号】：TP393.08

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