Fast clustering algorithm based on foregone samples in intrusion detections of mine security production
LIU Tao
HOU Yuan-bin
QI Ai-ling
CHANG Xin-tan
Abstract：; Aimed to network security problems was found in mine safety production information system, a fast clus-tering algorithm based on foregone samples for mixed data ( FCABFS) in network anomaly detections technology was proposed. Original clustering center was exactly obtained by FCABFS through training foregone samples; clustering center and non-similarity was calculated by separating objects. This algorithm solved problem of the higher false positive rate and the lower detection rate caused by using traditional clustering method with random selecting original clustering center and computing single attribute (continual or discrete) only in network anomaly detection. The experimental results compared with traditional clustering algorithm show that the detection rate is promoted 30% ,and the false positive rate is diminished 25%. This algorithm can also obtain detections to new type attack.
Keywords：network intrusionanomaly detectionclusteringk - means
Publication Date：2009-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1707-1712 )