posted on 2017-12-06, 00:00authored byAshley Chonka, W Zhou, J Singh, Yang Xiang
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 attracing 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.
Funding
Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)
History
Start Page
578
End Page
583
Number of Pages
6
Start Date
2008-01-01
ISBN-13
9780769531137
Location
Hong Kong
Publisher
IEEE Computer Society
Place of Publication
Los Alamitos, USA
Peer Reviewed
Yes
Open Access
No
Era Eligible
Yes
Name of Conference
IEEE International Conference on Pervasive Computing and Communications