Study On The Intrusion Detection System Based On Data Mining

The popularity of network application highlights its security, which makes problems concerning network security receive more and more attentions. With regard to the severe challenges, it is urgent to established a set of network security assurance system. The security question of the network receives the extensive concern more and more, technology and products that various kinds of network security are correlated with are emerging constantly. So it is urgent to establish a set of network security assurance system.It is becoming a very important task to protect computer system, network system and the whole Information Infrastructure, and to keep away from the intrusion. Network Security is a system conception; efficiency Security Policy is the first aim for Network Security, The Intrusion Detection is a new security technology, apart from tradition security protect technology, such as firewall and data crypt.It has been the focus of research. In nearly twenty years, researches on the Intrusion Detection, the core of Network Security, have been done at home and broad. Intrusion Detection Information Security, but it still has many problems, especially in self-completing and self-learning. To solve these problems, this thesis introduced elementary concept, principle and structure of intrusion detection and data mining technology. Based on the characteristic of IDS, this thesis applied the technology of data mining to it improved Apriori and sequential marshal pattern ,adopted one intrusion-detection system depending on data mining,and dicussed the crucial technology and solution to the realization of the system and the improved was introduced to the frame. In addition ,this thesis identified the characteristics, set up rules in response to the intrusion behavior, and matched these characteristics through processing auditing data. Finally the effecticeness of the improvwement is examplified specifically.