DDoS Detection and Prevention Based on Joint Entropy and Conditional Entropy

Abstract:

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Distributed Denial of Service (DDoS) imposes a very serious threat to the stability of the Internet. Compared with many detection approaches, detecting DDoS attacks based on entropy has advantages such as simplicity, high sensitivity and low false positive rate. But the method with single attribute entropy has high false positive rate when detecting attribute forged attacks. This paper presents a detecting method based on joint entropy and a filtering way based on conditional entropy. The efficiency of this scheme is validated with simulation on the research lab network.

Info:

Periodical:

Key Engineering Materials (Volumes 474-476)

Edited by:

Garry Zhu

Pages:

2129-2133

DOI:

10.4028/www.scientific.net/KEM.474-476.2129

Citation:

Y. H. Gu and W. M. Wu, "DDoS Detection and Prevention Based on Joint Entropy and Conditional Entropy", Key Engineering Materials, Vols. 474-476, pp. 2129-2133, 2011

Online since:

April 2011

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Price:

$35.00

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