Design of Gaussian Similarity Measure for Network Anomaly Detection

Abstract

Identifying intrusion in networks is one of the important concerns in computer networks. The task of dimensionality reduction and choice of classifier plays an important role in network intrusion detection. Dimensionality reduction should make sure that the efficacy of classifier on reduced dimensionality data is atleast retained if not improved. In this paper, we suggest a similarity function which can be used to find similarity between any two network elements expressed as vectors. The similarity measure is designed to make sure that the attribute distribution is taken into account for finding similarity value.