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25352 A two-tier system for web attack detection using linear discriminant method
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Tan, Zhiyuan and Jamdagni, Aruna and Nanda, Priyadarsi and He, Xiangjian and Liu, Ren Ping and Jia, Wenjing and Yeh, Wei-chang (2010) A two-tier system for web attack detection using linear discriminant method. In: Information and Communications Security. Lecture Notes in Computer Science 6476. Springer Verlag, Berlin, pp. 459-471. ISSN 0302-9743

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Official URL: http://dx.doi.org/10.1007/978-3-642-17650-0_32

Abstract

Computational cost is one of the major concerns of the commercial Intrusion Detection Systems (IDSs). Although these systems are proven to be promising in detecting network attacks, they need to check all the signatures to identify a suspicious attack in the worst case. This is time consuming. This paper proposes an efficient two-tier IDS, which applies a statistical signature approach and a Linear Discriminant Method (LDM) for the detection of various Web-based attacks. The two-tier system converts high-dimensional feature space into a low-dimensional feature space. It is able to reduce the computational cost and integrates groups of signatures into an identical signature. The integration of signatures reduces the cost of attack identification. The final decision is made on the integrated low-dimensional feature space. Finally, the proposed two-tier system is evaluated using DARPA 1999 IDS dataset for webbased attack detection.

Item Type:Book Section
Research Group:EWI-DIES: Distributed and Embedded Security
Research Program:CTIT-ISTRICE: Integrated Security and Privacy in a Networked World
Uncontrolled Keywords:Web-based attack, Intrusion detection, Packet payload, Feature selection, Linear discriminant method
ID Code:25352
Status:Published
Deposited On:28 November 2014
Refereed:Yes
International:Yes
More Information:statistics

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