Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23473
Title: A covariance analysis model for DDoS attack detection
Authors: Jin, S
Yeung, DS
Keywords: Computational complexity
Computer networks
Correlation methods
Covariance analysis
Telecommunication security
Telecommunication services
Telecommunication traffic
Issue Date: 2004
Publisher: IEEE
Source: 2004 IEEE International Conference on Communications, 20-24 June 2004, v. 4, p. 1882-1886 How to cite?
Abstract: This paper discusses the effects of multivariate correlation analysis on the DDoS detection and proposes an example, a covariance analysis model for detecting SYN flooding attacks. The simulation results show that this method is highly accurate in detecting malicious network traffic in DDoS attacks of different intensities. This method can effectively differentiate between normal and attack traffic. Indeed, this method can detect even very subtle attacks only slightly different from the normal behaviors. The linear complexity of the method makes its real time detection practical. The covariance model in this paper to some extent verifies the effectiveness of multivariate correlation analysis for DDoS detection. Some open issues still exist in this model for further research.
URI: http://hdl.handle.net/10397/23473
ISBN: 0-7803-8533-0
DOI: 10.1109/ICC.2004.1312847
Appears in Collections:Conference Paper

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