Host-based intrusion detection using statistical approaches

Abstract

An intrusion detection system (IDS) detects the malicious activities, running in the system that may be a single system or a networked system. Furthermore, the intrusion-based systems monitor the data in a system against the suspicious activities and also secure the entire network. Detection of malicious attacks with keeping acceptability of low false alarm rate is a challenging task in intrusion detection. In this paper, we analyze the three statistical approaches namely principal component analysis (PCA), linear discriminant analysis (LDA), and naive Bayes classifier (NBC), employed in host-based intrusion detection systems (HIDS) and we detect the accuracy rate using these approaches.