Research On Adaptation Intrusion Detection Model Based On Data Mining

In recent years, internet service developed rapidly, enjoying infor_ mation sharing of the internet service , people have to suffer from net security problem which becomes more and more severe. The tradition strategy has a ability not equal to one' s ambition when intrusion' s types change regularily, it can' t satisfy the need of net security any more. Intrusion detecion has become a strong barrier to defend net intrusion because of initiative recovery strategy of focusing on data analyzing. Data mining , a effective technique in data analyzing, is naturally applied in intrusion detection. Therefore , researching of intrusion detection system basing on data mining become more and more hot.In order to solve some issue on intrusion detection , this article focus on designing a adaptive intrusion detection model on the base of others' relation research. We employ adaptation space to describe adaptation strategy, which includes condition space and tactic space. Condition space is made of states of security environment and tactic space is made of intrusion detection strategies. We use control chart to characterize states of security environment and data mining to construct intrusion detection strategies. The latter includes pattern mining, pattern consolidation arid pattern comparing. In succession to it, we construct attribute set and training set for classification of net data. Follow that we construct tactic space, and offer the algorithm. According to the adaptation strategy we design a adaptive intrusion detection model, DAIDS. In the last we describe the relational experimentations and analyse the result of the experimentations.