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Intelligent DDoS packet filtering in high-speed networks

Xiang, Yang and Zhou, Wanlei 2005, Intelligent DDoS packet filtering in high-speed networks, Lecture notes in computer science, vol. 3758, pp. 395-406.

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Title Intelligent DDoS packet filtering in high-speed networks
Author(s) Xiang, YangORCID iD for Xiang, Yang
Zhou, WanleiORCID iD for Zhou, Wanlei
Journal name Lecture notes in computer science
Volume number 3758
Start page 395
End page 406
Publisher Springer-Verlag
Place of publication Berlin, Germany
Publication date 2005
ISSN 0302-9743
Summary Currently high-speed networks have been attacked by successive waves of Distributed Denial of Service (DDoS) attacks. There are two major challenges on DDoS defense in the high-speed networks. One is to sensitively and accurately detect attack traffic, and the other is to filter out the attack traffic quickly, which mainly depends on high-speed packet classification. Unfortunately most current defense approaches can not efficiently detect and quickly filter out attack traffic. Our approach is to find the network anomalies by using neural network, deploy the system at distributed routers, identify the attack packets, and then filter them quickly by a Bloom filter-based classifier. The evaluation results show that this approach can be used to defend against both intensive and subtle DDoS attacks, and can catch DDoS attacks’ characteristic of starting from multiple sources to a single victim. The simple complexity, high classification speed and low storage requirements make it especially suitable for DDoS defense in high-speed networks.
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
Copyright notice ©2005, Springer-Verlag
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Document type: Journal Article
Collection: School of Information Technology
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