![](/images/graphics-bg.png)
Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM
Joint Authors
Ganapathy, Sannasi
Kannan, A.
Yogesh, Palanichamy
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-09-27
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively.
However, most of these systems are able to detect the intruders only with high false alarm rate.
In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods.
For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time.
Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing.
The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set.
American Psychological Association (APA)
Ganapathy, Sannasi& Yogesh, Palanichamy& Kannan, A.. 2012. Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM. Computational Intelligence and Neuroscience،Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-503195
Modern Language Association (MLA)
Ganapathy, Sannasi…[et al.]. Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM. Computational Intelligence and Neuroscience No. 2012 (2012), pp.1-10.
https://search.emarefa.net/detail/BIM-503195
American Medical Association (AMA)
Ganapathy, Sannasi& Yogesh, Palanichamy& Kannan, A.. Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM. Computational Intelligence and Neuroscience. 2012. Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-503195
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-503195