Anomaly Detection on Intrusion Detection System Using Clique Partitioning
Anomaly Detection on Intrusion Detection System Using Clique Partitioning
Author : NUNGKY NASTAIINULLAH; ADIWIJAYA; ANGELINA PRIMA KURNIATI Published on : ICoICT 2014 (Universitas Telkom - Bandung, Indonesia)
Abstract
The development of information and network technology makes network security become important. Intrusion is one of the issue in network security. To prevent intrusion happens, intrusion detection system (IDS) is built. One of IDS category is anomaly detection. This category detects intrusion event based on data profile. Clustering is one way to observe data profile. There???s a lot of clustering algorithm proposed for anomaly detection on IDS, one of them is CLIQUE Partitioning (CP). Testing is done to analyze system???s performance based on computational time, completeness, and false alarm rate. CP algorithm shows good performance from completeness point of view (94.59%) and false alarm rate (2.54%). From computational time, CP shows good performance based on the amount of tuple, but the performance is not too good from the quantity of feature side.
