Matrix Factorization Approach for Feature Deduction and Design of Intrusion Detection Systems

Abstract

Current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (if anything) to the detection process. The purpose of this research is to identify important input features in building an IDS that is computationally efficient and effective. This paper propose a novel matrix factorization approach for feature deduction and design of intrusion detection systems. Experiment results indicate that the proposed method is efficient.