基于BAM网络和遗传免疫的入侵检测算法  

Intrusion detection measurement based on BAM network and heredity immunity

作　　者：龙鹏飞[1] 宋振[1] 

机构地区：[1]长沙理工大学计算机与通信工程学院,湖南长沙410076

出　　处：《计算机工程与设计》2007年第12期2793-2796,共4页Computer Engineering and Design

基　　金：湖南省自然科学基金项目(Q3JJY3101);湖南省科技计划基金项目(04FJ4130)

摘　　要：通过结合人体免疫系统的出色功能和免疫原理在网络入侵检测模型中的应用,将遗传算法和BAM网络嵌入其中,提高了数据检测的匹配速度和检测子的覆盖率,使得入侵检测系统的检测率、误报率及漏报率得到明显的改观。从仿真试验中可以看出,相比单一应用人工免疫的入侵检测算法,该算法有较强的多样性、适应性和鲁棒性等优良特性。Combined with the application of excellent property of humanity immunity system and immune principles in the model of network intrusion detection, adding heredity algorithm and BAM network to the model promote the matching rate of data detection and percentage of coverage of detector, and mend the detection rate, misinformation rate and non-disclosure rate of intrusion detection system. Through virtual test, compared with intrusion detection algorithm in which only hand-actuated immunity is applied, the introduced algorithm is more diverse, adaptable and of robustness.

关 键 词：入侵检测 免疫原理 BAM网络 遗传算法 检测子 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]