NDLI: Dimension Reduction in Intrusion Detection Using Manifold Learning

Content Provider	IEEE Xplore Digital Library
Author	Kai-mei Zheng Xu Qian Pei-chong Wang
Copyright Year	2009
Abstract	Manifold learning is an emerging and promising approach in nonlinear dimension reduction. Representative methods include locally linear embedding (LLE) and Isomap. However, both methods fail to guarantee connectedness of the constructed neighborhood graphs. We propose k variable method called kv-LLE and kv-Isomap to build connected neighborhood graphs so as to enhance the robustness. The applicability of above two modified dimension reduction methods is examined by combining with the classifier of one class SVM. We evaluate new schemes with the KDD dataset and UNM dataset. Experiment results demonstrate higher detection rate and significant lower false positive rate on kv-Isomap method. The kv-LLE method is more suitable for kinds of text classification tasks. And the algorithm kv-Isomap performs much better than kv-LLE. We also have an unexpected gain in marking singular points.
Starting Page	464
Ending Page	468
File Size	302149
Page Count	5
File Format	PDF
ISBN	9781424454112
e-ISBN	9781424454129
DOI	10.1109/CIS.2009.116
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	kv-LLE intrusion detection Data mining dimension reduction kv-Isomap manifold learning Support vector machines Manifolds Text categorization Intrusion detection Information security Support vector machine classification Feature extraction Robustness Computational intelligence
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Intrusion Detection Using Isomap and Support Vector Machine

Supervised Non-Linear Dimensionality Reduction Techniques for Classification in Intrusion Detection

A method based on manifold learning and Bagging for text classification

Keyword extraction for text categorization

An intrusion detection method based on SVM and KPCA

Local Information Based Overlaid Text Detection by Classifier Fusion

Support Vector Machines for Anomaly Detection

Intrusion Detection Model Based on Improved Support Vector Machine

High Efficient Intrusion Detection Methodology with Twin Support Vector Machines

Dimension Reduction in Intrusion Detection Using Manifold Learning

Similar Documents

Intrusion Detection Using Isomap and Support Vector Machine

Supervised Non-Linear Dimensionality Reduction Techniques for Classification in Intrusion Detection

A method based on manifold learning and Bagging for text classification

Keyword extraction for text categorization

An intrusion detection method based on SVM and KPCA

Local Information Based Overlaid Text Detection by Classifier Fusion

Support Vector Machines for Anomaly Detection

Intrusion Detection Model Based on Improved Support Vector Machine

High Efficient Intrusion Detection Methodology with Twin Support Vector Machines

Dimension Reduction in Intrusion Detection Using Manifold Learning