New Intrusion Detection Based on Threshold Clustering and KNN Algorithm
Ning Liu · Journal of Zhengzhou University · 2010
A guidance clustering of labeled empirical data is studied using threshold-based clustering.The main target of clustering is to compress huge training dataset to the limited number of clustering centroids,to solve the problem of sample selection in KNN classification algorithm,and discover isolated point.A smaller number of more representative clustering centroids are used in place of the original huge sample dataset of KNN algorithm.Then,the clustering density is used to revise KNN classification algorithm to improve the detection accuracy and detection speed.