A Framework for an Adaptive Anomaly Detection System with Fuzzy Data Mining

• Published in: Wuhan University journal of natural sciences Vol. 11; no. 6; pp. 1797 - 1800
• Main Authors: Xiang, Gao, Min, Wang, Rongchun, Zhao
• Format: Journal Article
• Language: English
• Published: School of Computer, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China 01.11.2006
• Subjects: 侵入检测; 异常检测; 数据挖掘; 模糊集; 网络安全; intrusion detection; anomaly detection; network security; unsupervised; fuzzy cluster

In this paper, we present an adaptive anomaly detection framework that isapplicable to network-based intrusion detection. Our framework employs fuzzy cluster algorithm to detect anomalies in an online, adaptive fashion without a priori knowledge of the underlying data. We evaluate our method by perf...