NDLI: Incremental Learning Algorithm based on Support Vector Machine with Mahalanobis distance (ISVMM) for intrusion prevention

Content Provider	IEEE Xplore Digital Library
Author	Myint, H.O. Meesad, P.
Copyright Year	2009
Description	Author affiliation: Department of Teacher Training in Electrical Engineering, Faculty of Technical Education, King Mongkut's University of Technology North Bangkok (KMUTNB), Thailand (Meesad, P.) \|\| Department of Information Technology, Faculty of Information Technology, King Mongkut's University of Technology North Bangkok (KMUTNB), Thailand (Myint, H.O.)
Abstract	In this paper we propose a new classifier called an Incremental Learning Algorithm based on Support Vector Machine with Mahalanobis distance (ISVMM). Prediction of the incoming data type by supervised learning of Support Vector Machine (SVM), reducing the step of calculation and complexity of the algorithm by finding a support set, error set and remaining set, providing of hard and soft decisions, saving the time for repeatedly training the datasets by applying the incremental learning, a new approach for building an ellipsoidal kernel for multidimensional data instead of a sphere kernel by using Mahalanobis distance, and the concept of handling the covariance matrix from dividing by zero are various features of this new algorithm. To evaluate the classification performance of the algorithm, it was applied on intrusion prevention by employing the data from the third international knowledge discovery and data mining tools competition (KDDcup'99). According to the experimental results, ISVMM can predict well on all of the 41 features of incoming datasets without even reducing the enlarged dimensions and it can compete with the similar algorithm which uses a Euclidean measurement at the kernel distance.
Starting Page	630
Ending Page	633
File Size	1386842
Page Count	4
File Format	PDF
ISBN	9781424433872
DOI	10.1109/ECTICON.2009.5137129
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-06
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intrusion Prevention Educational technology Support Vector Machine Data mining Mahalanobis Information technology Support vector machines Incremental Learning Supervised learning Support vector machine classification Intrusion detection Machine learning Euclidean distance Euclidean Kernel
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

Multi-class support vector machines based on the mahalanobis distance

Incremental Learning In the Application of Intrusion Detection

Weighted Mahalanobis Distance Kernels for Support Vector Machines

Notice of RetractionStudy on advanced variance-considered machines using Mahalanobis distance

Network intrusion detection method based on Agent and SVM

Modified Ant Miner for Intrusion Detection

An improved feature selection algorithm based on MAHALANOBIS distance for Network Intrusion Detection

Intrusion Detection System Based on Improved SVM Incremental Learning

A New Feature Extraction Method of Intrusion Detection

Incremental Learning Algorithm based on Support Vector Machine with Mahalanobis distance (ISVMM) for intrusion prevention

Similar Documents

Multi-class support vector machines based on the mahalanobis distance

Incremental Learning In the Application of Intrusion Detection

Weighted Mahalanobis Distance Kernels for Support Vector Machines

Notice of RetractionStudy on advanced variance-considered machines using Mahalanobis distance

Network intrusion detection method based on Agent and SVM

Modified Ant Miner for Intrusion Detection

An improved feature selection algorithm based on MAHALANOBIS distance for Network Intrusion Detection

Intrusion Detection System Based on Improved SVM Incremental Learning

A New Feature Extraction Method of Intrusion Detection

Incremental Learning Algorithm based on Support Vector Machine with Mahalanobis distance (ISVMM) for intrusion prevention