Research On Application Of Intrusion Detection Based On Improved FCM

Intrusion detection system which succeeds to the traditional safe measures, such as firewall, data encryption and so on is a kind of new safe protective technology. As a kind of active safe technology, intrusion detection system has recently been researching hot.This paper first introduces concept and technology of intrusion detection and related theory of data mining, making the readers have further understanding of methods and concepts of intrusion detection and data mining algorithms. And then analyze clustering algorithm in depth, and put forward intrusion detection algorithm based on improved fuzzy C means (AMCA-FCM) algorithm and execute the anomaly detection on KDDCUP data set, finally build intrusion detection system based improved algorithm and analyze the feasibility of the system. Study data processing step in data preparation module and give out specific continuous method and formulas of normalization and standardization. At the same time, put forward improved fuzzy C means algorithm in the light of clustering effects of fuzzy C means algorithm depending on selection of the initial value, solve the problem that the algorithm sensitive to selection of the initial values and easily to fall in the local best solution. Thereby under the condition guarantee integrality and consistency of data attribute values, get rid of blindness of selecting initial value and reduce clustering time and algorithm complexity, enhance speed of the algorithm. Finally, compared the proposed intrusion detection model with existing data mining intrusion detection model,verified that the model is suitable.