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Detecting and tracing DDoS attacks by intelligent decision prototype

Chonka, Ashley, Zhou, Wanlei, Singh, Jaipal and Xiang, Yang 2008, Detecting and tracing DDoS attacks by intelligent decision prototype, in Proceedings of the 6th Annual IEEE International Conference on Pervasive Computing and Communications, IEEE, Piscataway, N.J., pp. 578-583.

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Title Detecting and tracing DDoS attacks by intelligent decision prototype
Author(s) Chonka, Ashley
Zhou, Wanlei
Singh, Jaipal
Xiang, Yang
Conference name IEEE International Conference on Pervasive Computing and Communications (6th : 2008 : Hong Kong)
Conference location Hong Kong
Conference dates 17-21 March 2008
Title of proceedings Proceedings of the 6th Annual IEEE International Conference on Pervasive Computing and Communications
Editor(s) [Unknown]
Publication date 2008
Conference series International Conference on Pervasive Computing and Communications
Start page 578
End page 583
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) fecision trees
fistributed fenial of service
IP traceback
intelligent fecision prototype
machine learning
Summary Over the last couple of months a large number of distributed denial of service (DDoS) attacks have occurred across the world, especially targeting those who provide Web services. IP traceback, a counter measure against DDoS, is the ability to trace IP packets back to the true source/s of the attack. In this paper, an IP traceback scheme using a machine learning technique called intelligent decision prototype (IDP), is proposed. IDP can be used on both probabilistic packet marking (PPM) and deterministic packet marking (DPM) traceback schemes to identify DDoS attacks. This will greatly reduce the packets that are marked and in effect make the system more efficient and effective at tracing the source of an attack compared with other methods. IDP can be applied to many security systems such as data mining, forensic analysis, intrusion detection systems (IDS) and DDoS defense systems.
ISBN 076953113X
Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2008, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30018161

Document type: Conference Paper
Collections: School of Engineering and Information Technology
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