基于人工免疫的入侵检测改进模型研究

Study on Improved Model of Intrusion Detection Based on Artificial Immunization

在前人提出的基于人工免疫的入侵检测模型的基础上,加入了抗体精度匹配阀值和粗糙匹配频度阀值以改进其算法中对于self-nonself的判断处理方法,使得对于正常的突发性网络事件也可以进行合理的判断,从而加强了对网络事件检测的灵活性,并提出了改进后的入侵检测与防御体系模型.最后通过仿真测试,证明本模型在对突发性网络事件判断的灵活性、合理性和可行性,优于前人的基于人工免疫的入侵检测模型.

Based on a former invasion detection model of artificial immunization, the match values of immune body precision and rough match frequency are added to improve the self - nonself judgment and processing method of this algorithm and to enable it to carry on reasonable judgment of the common sudden network events,which also strengthens the flexibility of network event detection. An improved invasion and defensive model is then proposed. Finally, through simulation test, the flexibility, feasibility and rationality of this model on the burst network events is confirmed, which surpasses the former invasion detection model based on the artificial immune.