Intrusion Detection Based on Boosting Fuzzy Classification
Limin Xia · Jisuanji gongcheng · 2008
This paper proposes a method for intrusion detection based on Boosting fuzzy classification. Fuzzy rules involved in intrusion detectionare obtained by genetic algorithm, and Boosting algorithm is employed to change the distribution of training instances during each round of training,so that new fuzzy classification rules extracted by genetic algorithm will put more emphasis upon the instances misclassified or uncovered.Simulation experiments with the data set kddcup’99 show that the method has good recognition performance.