Research On Anomaly Intrusion Detection Based On Data Mining

With the increase of informatization level and enhancement of dependence on computer networks for human society, how to keep informatization society running normally, safely and steadily is the most important issue of which computer network safety is one to be always strengthened and improved. At present, application of interconnected network is extensively extended and its open characteristic is extensively strengthened, which causes more and more network systems exposed to threat of attacks and intrusions.Intrusion Detection is a security technology to detect the intrusion through monitoring the target system in runtime. Based on the research on the intrusion detection technology and intrusion method in common use, a solution of runtime anomaly Intrusion Detection System based on data mining is proposed in the paper. Aimed at the characteristics of network intrusion and attacks, the system monitors the data packet through association analysis algorithm in data mining method to analyze the connection record.In connection record analysis, the standard Apriori algorithm is modified and the influence caused by outlying factors is eliminated according to the circumstantialities in intrusion detection, whose validity and feasibility is approved by field test. An intrusion detection mechanism adapted to the current circumstances, which can enhance the intrusion detection speed and lower the system resources usage.