NDLI: Intrusion Detection System by Integrating PCNN and Online Robust SVM

Content Provider	IEEE Xplore Digital Library
Author	Hengjie Li Jiankun Wang
Copyright Year	2007
Description	Author affiliation: Gansu Lianhe Univ., Lanzhou (Hengjie Li)
Abstract	This paper proposes the application of principal component neural networks for intrusion feature extractions, the extracted features are employed by online robust SVM for classification. The MIT's KDD Cup 99 dataset is used to evaluate the proposed method compared to conventional SVMs, ANN and KNN in separating normal usage profiles from intrusive profiles of computer programs, which clearly demonstrates that PCNN-based feature extraction method can greatly reduce the dimension of input space without degrading or even boosting the classification performance, and indicates the superiority of online Robust SVM not only can achieve high intrusion detection accuracy and low false positives but also can be trained online and the results outperform the original ones with fewer support vectors and less training time without decreasing detection accuracy. Both of these achievements could significantly benefit an effective online intrusion detection system.
Starting Page	250
Ending Page	254
File Size	366892
Page Count	5
File Format	PDF
ISBN	9780769529431
DOI	10.1109/NPC.2007.131
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Degradation High performance computing Neural networks Intrusion detection Support vector machine classification Artificial neural networks Feature extraction Robustness Application software
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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