A multiple-criteria quadratic programming approach to network intrusion detection

Authors:
Gang Kou;Yi Peng;Yong Shi;Zhengxin Chen;Xiaojun Chen
Affiliations:
College of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE;College of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE;College of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE;College of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE;Faculty of Science and Technology, Hirosaki University, Hirosaki, Japan
Venue:
CASDMKM'04 Proceedings of the 2004 Chinese academy of sciences conference on Data Mining and Knowledge Management
Year:
2004

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Abstract

The early and reliable detection and deterrence of malicious attacks, both from external and internal sources are a crucial issue for today’s e-business. There are various methods available today for intrusion detection; however, every method has its limitations and new approaches should still be explored. The objectives of this study are twofold: one is to discuss the formulation of Multiple Criteria Quadratic Programming (MCQP) approach, and to investigate the applicability of the quadratic classification method to the intrusion detection problem. The demonstration of successful Multiple Criteria Quadratic Programming application in intrusion detection can add another option to network security toolbox. The classification results are examined by cross-validation and improved by an ensemble method. The results demonstrated that MCQP is excellent and stable. Furthermore, the outcome of MCQP can be improved by the ensemble method.