An abnormal-based approach to effectively detect DDOS attacks

Li, Ke and Zhou, Wanlei 2009, An abnormal-based approach to effectively detect DDOS attacks, Journal of the Chinese institute of engineers, vol. 32, no. 7, pp. 889-895.

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Title An abnormal-based approach to effectively detect DDOS attacks
Author(s) Li, Ke
Zhou, WanleiORCID iD for Zhou, Wanlei
Journal name Journal of the Chinese institute of engineers
Volume number 32
Issue number 7
Start page 889
End page 895
Total pages 7
Publisher Chinese Institute of Engineers
Place of publication Taipei City Taiwan, Republic of China
Publication date 2009
ISSN 0253-3839
Keyword(s) DDoS
Generalized entropy
Attacks detection
Summary Distributed Denial-of-Service (DDoS) attacks are a serious threat to the safety and security of cyberspace. In this paper we propose a novel metric to detect DDoS attacks in the Internet. More precisely, we use the function of order α of the generalized (Rényi) entropy to distinguish DDoS attacks traffic from legitimate network traffic effectively. In information theory, entropies make up the basis for distance and divergence measures among various probability densities. We design our abnormal-based detection metric using the generalized entropy. The experimental results show that our proposed approach can not only detect DDoS attacks early (it can detect attacks one hop earlier than using the Shannon metric while order  α =2, and two hops earlier than the Shannon metric while order α =10.) but can also reduce both the false positive rate and the false negative rate, compared with the traditional Shannon entropy metric approach.
Language eng
Field of Research 080503 Networking and Communications
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2009
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Document type: Journal Article
Collection: School of Information Technology
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