摘要
基于否定选择的网络入侵检测系统中,检测器集的质量在很大程度上影响检测速率和检测准确率。基于小生境原理,对根据否定选择算法生成的检测器集中存在的重叠检测器进行高频变异和低频变异,提高了检测器集对非自体空间的覆盖率。根据否定选择算法的仿真实验的结果表明优化后的检测器集的整体检测效率明显改善。
Based on the negative selection,the quality of detectors collection plays a decisive role in the examining speed and the rate of accuracy in network invasion examination system.According to microhabitat principle and the existence of overlap detectors in detectors collection produced by the negative selection algorithm,the high frequency variation and the low frequency variation are carried out to enhance the coverage fraction of detectors collection to the unself space.The paper gives simulation algorithm.Experimental results show that the whole set of optimized detector has higher efficiency.
出处
《广东石油化工学院学报》
2011年第3期57-60,共4页
Journal of Guangdong University of Petrochemical Technology
关键词
人工免疫
小生境
否定选择
artificial immunity
the microhabitat
negative selection
