Intrusion Detection Method Based on LEGClust Algorithm
Yi Lin Zhao, Qing Lei Zhou · Applied Mechanics and Materials · 2012
Clustering analysis is a typical unsupervised learning technology in data mining, which can improve the efficiency of intrusion detection system. LEGClust cluster algorithm is a new clustering analysis technique and it can effectively find the arbitrary shape clusters hidden in the data. We apply this algorithm to the intrusion detection field and present an intrusion detection method. We introduce the real dissimilarity among data into the determination of data connection relationship. Experiment results on KDD CUP1999 Dataset show that LEGClust algorithm is an effective technique for intrusion detection and the improved LEGClust performs even better.