Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
460357 | Journal of Network and Computer Applications | 2007 | 19 Pages |
Abstract
The process of monitoring the events occurring in a computer system or network and analyzing them for sign of intrusions is known as intrusion detection system (IDS). This paper presents two hybrid approaches for modeling IDS. Decision trees (DT) and support vector machines (SVM) are combined as a hierarchical hybrid intelligent system model (DT–SVM) and an ensemble approach combining the base classifiers. The hybrid intrusion detection model combines the individual base classifiers and other hybrid machine learning paradigms to maximize detection accuracy and minimize computational complexity. Empirical results illustrate that the proposed hybrid systems provide more accurate intrusion detection systems.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Sandhya Peddabachigari, Ajith Abraham, Crina Grosan, Johnson Thomas,