Paper Info
Title
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.
Year
DOI
Venue
2015
10.1007/978-81-322-2695-6_40
PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON FRONTIERS IN INTELLIGENT COMPUTING: THEORY AND APPLICATIONS (FICTA) 2015
Keywords
DocType
Volume
Principal component analysis (PCA),Linear discriminant analysis (LDA),Naive bayes classifier (NBC),Host-based intrusion detection systems (HIDSs)
Conference
404
ISSN
Citations 
PageRank 
2194-5357
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Sunil Kumar Gautam100.34
H. Om29917.56