T2 Control Chart based on Successive Difference Covariance Matrix for Intrusion Detection System

Abstract

The Intrusion detection is a process to monitor the events taking place in a computer system or network and analyze the monitoring results to find signs of intrusion. One of alternative solutions for intrusion detection is the usage of statistical methods that Statistical Process Control especially the control charts.. In this research, the Hotelling’s T2 chart performance for intrusion detection is improved using the Successive Difference Covariance Matrix where the control limits will be calculated using Kernel Density Estimation. The proposed method using T2 based on Kernel Density Estimation control limit outperforms other approaches both in training and testing dataset.