基于免疫遗传的伪装入侵检测

Masquerade intrusion detection algorithm with immune and genetic

为了有效应对网络伪装入侵,提出了一种基于免疫遗传理论的伪装入侵检测算法,给出了入侵检测中抗体和抗原的形式化定义,建立遗传算子的数学模型以及抗体种群进化的递推方程,最后给出了入侵检测过程。理论分析和实验结果表明,该算法具有较好的鲁棒性和自适应能力,以及搜索和优化性能优异,能够在一定程度提高入侵检测的命中率,并取得较小的误报率,为伪装入侵检测提供了一种新的解决方案。

To response effectively the masquerade intrusion of network,an algorithmbased immune and genetic formasquerade intrusion detection is presented.First of all,the formal definitions of antibodies and antigens are introduced.Afterward,the mathematicalmodel of genetic operators is established as well as the evolution equation of antibodies populations.Finally,the process of intrusion detection is presented.Both the theoretical analysis and experimental results show that the algorithm has better robustness and adaptive capacity. The performance of search and optimization of algorithm are higher than other methods.It achieves better hit rate and lower false alarm. In this way,a new solution for masquerade intrusion detection is provided.