Design and implementation of intrusion detection system based on honeypot
基于蜜罐的入侵检测系统的设计与实现*

The traditional IDS (intrusion detection system) can not identify the unknown attacks. Therefore, this paper introduced honeypot technique into the IDS. It desigaed a intrusion detection system based on ANN (artificial neural network) . It constructed the system contained FDM detection model and SDM detection model by using perceptron learning method. FDM was used to distinguish the attack class from the normal class, while the other focused on detecting some main types of attacks. At last, an experiment was to test detection ability of HoneypotIDS. The results of the experiment show that HoneypotIDS has a better detection rate and a lower false positive rate for the intrusion activities in the monitored network.