NDLI: Intrusion detection model with twin support vector machines

Content Provider	Springer Nature Link
Author	He, Jun Zheng, Shi hui
Copyright Year	2014
Abstract	Intrusion detection system (IDS) is becoming a critical component of network security. However, the performance of many proposed intelligent intrusion detection models is still not competent to be applied to real network security. This paper aims to explore a novel and effective approach to significantly improve the performance of IDS. An intrusion detection model with twin support vector machines (TWSVMs) is proposed. In this model, an efficient algorithm is also proposed to determine the parameter of TWSVMs. The performance of the proposed intrusion detection model is evaluated with KDD’99 dataset and is compared with those of some recent intrusion detection models. The results demonstrate that the proposed intrusion detection model achieves remarkable improvement in intrusion detection rate and more balanced performance on each type of attacks. Moreover, TWSVMs consume much less training time than standard support vector machines (SVMs).
Starting Page	448
Ending Page	454
Page Count	7
File Format	PDF
ISSN	10071172
Journal	Journal of Shanghai Jiaotong University (Science)
Volume Number	19
Issue Number	4
e-ISSN	19958188
Language	English
Publisher	Shanghai Jiaotong University Press
Publisher Date	2014-08-05
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	network security twin support vector machine (TWSVM) parameter determination Electrical Engineering Materials Science Computer Science Architecture Life Sciences
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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

A probability approach to anomaly detection with twin support vector machines

Erratum to: A pRobability Approach to Anomaly Detection with Twin Support Vector Machines

High Efficient Intrusion Detection Methodology with Twin Support Vector Machines

Application of support vector machine to ship steering

Masquerade detection using support vector machine

Support vector machine-based fuzzy rules acquisition system

Distributed Intrusion Detection System in a Multi-Layer Network Architecture of Smart Grids

Intrusion Detection Model Based on Improved Support Vector Machine

Support vector classifiers and network intrusion detection

Intrusion detection model with twin support vector machines

Similar Documents

A probability approach to anomaly detection with twin support vector machines

Erratum to: A pRobability Approach to Anomaly Detection with Twin Support Vector Machines

High Efficient Intrusion Detection Methodology with Twin Support Vector Machines

Application of support vector machine to ship steering

Masquerade detection using support vector machine

Support vector machine-based fuzzy rules acquisition system

Distributed Intrusion Detection System in a Multi-Layer Network Architecture of Smart Grids

Intrusion Detection Model Based on Improved Support Vector Machine

Support vector classifiers and network intrusion detection

Intrusion detection model with twin support vector machines