Network Intrusion Detection Algorithm Based on Unsupervised Immune Hierarchical Optimization
一种基于无监督免疫优化分层的网络入侵检测算法

When the external network accesses university network, the external network data has no category tags, so the data recognition is unclear. I}he traditional intrusion detection model can not effectively extract the identifying char- acteristics of the unsupervised external network accessing data, and intrusion detection model can not be accurately trained, which makes accuracy of the college network intrusion detection is not high. I}o solve this problem, this paper proposed a intrusion detection algorithm based on unsupervised immune hierarchical optimization to learn data in the immune network,complete the data compression using the small-scale network,focus on improving the identifying cha racteristics of the data, and analyze the network using hierarchical clustering method to complete the establishment of the data model. Simulation results show that this unsupervised intrusion detection model method overcomes the obvious identifying characteristics of the university external network accessing data, and improves the accuracy of the university network intrusion detection,achieves satisfactory results.