Presentation 2008/5/8
Entropy-based Input-Output Traffic Mode Detection Scheme for DoS/DDoS Attacks
Zhang Fengxiang, Shunji ABE,
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Abstract(in English) Nowadays Distributed Denial of Service (DDoS) attacks are threatening the widely used Internet. How to detect DDoS attacks quickly and effectively becomes an important and challenging work. Many detection schemes based on traffic distribution have been proposed, but problems are still remaining. The real Internet traffic is changefully and not easily modeled in a short term. Studying the characteristics of traffic distribution is a popular considering way; however these kinds of schemes need a relatively long observation time to decide statistics property. This will mitigate detection scheme's efficiency. In our paper we have studied the network node's Input-Output traffic and proposed a relatively simple traffic analyses model, named "8 Input-Output Modes Model"(8-IOMM). Based on this new model, we have adopted an entropy-based scheme to detect out DDoS attacks. We've tested the scheme with the typical Internet traffic from Science Information Network and the DDoS attack data from OPNET simulation tool! The results show that our detection scheme works efficiently.
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Keyword(in English) Distributed denial of services attacks / Anomaly detection / 8 Input-output modes / Sample entropy
Paper # NA2008-2
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Committee NS
Conference Date 2008/5/8(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Entropy-based Input-Output Traffic Mode Detection Scheme for DoS/DDoS Attacks
Sub Title (in English)
Keyword(1) Distributed denial of services attacks
Keyword(2) Anomaly detection
Keyword(3) 8 Input-output modes
Keyword(4) Sample entropy
1st Author's Name Zhang Fengxiang
1st Author's Affiliation Department of Informatics, Graduate University()
2nd Author's Name Shunji ABE
2nd Author's Affiliation National Institute of Informatics
Date 2008/5/8
Paper # NA2008-2
Volume (vol) vol.108
Number (no) 31
Page pp.pp.-
#Pages 6
Date of Issue