Research And Application Of Intrusion Detection Based On Data Mining

People have more and more concerned about the network security. Traditional safe protection technology which adopts identification & authentication, access controlling and technology of cryptography cannot prevent the intrusion behavior which invade into the unauthorized behavior computer system by utilizing computer defect of software and hardware of system, and the technology of the fire wall can't deal with the endless defect of application designing and the attack which access the encrypted passway. the technology is necessary that can find and report the system intrusion behavior, namely intrusion detection.Nevertheless, the traditional intrusion detection technique cannot deal with more and more complicated attack on the way of expansibility and adaptability. The knowledge of many other fields is introduced, and the data mining is a kind of hotter technology among them. The data mining is to excavate out the potential and the valuable information from a large number of data.Therefore, on the base of the traditional intrusion detection technology, this thesis utilizes data-mining technology, and propose an advanced large scale coordinating distributed intrusion detection system model, which is based on host computer and network, then proposed a model of setting up feature, which completely applied data mining method and fits for such mixed model during data pretreated phase. It analyses the realization frame, provides new weighting association rules and alternate series analysis, and apply them in the course of intrusion detection technology. This system has self-adaptability and strong extendable feature, and realizes low error detecting rate and misinformation rate. Thus, it achieves the goal of improving intrusion detection quality, and has widely application value.