Single Pass Anomaly Detection In Network

Anomaly detection in networks is detection of deviations from what is considered to be normal. Performing anomaly detection is a learning approach to detect failures and intrusions in a network, intended to capture novel attacks. Anomaly Detection With fast Incremental Clustering (ADWICE) is an efficient algorithm to detect anomaly. But, since it uses distance based clustering mechanism it suffers from inefficient clustering. We have proposed some additional density based statistical variables and also proposed to change the clusters’ shape in the form of box pattern, so as to improve the efficiency. We have also implemented Generalized Incremental Clustering (GenIc) algorithm and Tree-Based algorithm for anomaly detection. These are single pass anomaly detection algorithms.