Application of improved Apriori-TFP algorithm in intrusion detection
Shaohua Teng · Jisuanji gongcheng yu sheji · 2011
To discover potential and effective intrusion detection rules from test data,and improve the detection rate of intrusion detection system,a model of intrusion detection system based on class-association rule(CAR) is presented.Firstly,the datasets are preprocessed by the system,and then all the CARs are generated by the use of the improved mining algorithm of CAR: I-Apriori-TFP(total-from-partial).Moreover,a classifier based on the generated CARs is established and it is tested by test data so as to generate a detection agent.Finally,network data are detected by the detection agent.Experiments show that the proposed method could detect intrusions efficiently in the network.