基于人工免疫的集成入侵检测模型  

Integrated intrusion detection model based on artificial immunity

作　　者：辛壮 万良[1] XIN Zhuang;WAN Liang(College of Computer Science and Technology,Guizhou University,Guiyang 550025,China)

机构地区：[1]贵州大学计算机科学与技术学院

出　　处：《计算机工程与设计》2019年第10期2799-2804,共6页Computer Engineering and Design

基　　金：贵州省科学基金项目(黔科合J字[2011](No.2328)、黔科合LH字[2014](No.7634))

摘　　要：为降低网络数据流量冗余属性对入侵检测效果的影响,提高入侵检测检测率,设计一种基于人工免疫的集成入侵检测模型,基于该模型提出一种疫苗提取与接种的策略。使用粗糙集方法获取优良抗体,结合异常检测与误用检测对模型进行扩展,疫苗提取与接种策略保证抗体的优良性能够得到遗传。与传统人工免疫模型相比,该模型收敛速度更快、检测率更高。通过实验验证了该模型在入侵检测方面有较好的检测结果。To reduce the effects of redundancy attribute of data traffic on intrusion detection in network and improve detection rate of intrusion detection,based on artificial immune system,an integrated intrusion detection model was designed.According to the model,a strategy on vaccine extraction and vaccination was proposed.The rough set method was used to obtain good antibodies.Combined with abnormal detection and misuse detection,by expanding the model of abnormal detection and misuse detection,vaccine extraction and vaccination strategy ensured that the superiority of the antibody could be inherited.Compared with the traditional artificial immune model,the proposed model has higher convergence speed and detection rate.Experimental results show that the proposed model is of better detection results in intrusion detection.

关 键 词：人工免疫 粗糙集 入侵检测 疫苗 集成入侵检测模型 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]