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Detecting and tracing DDoS attacks by Intelligent Decision Prototype

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conference contribution
posted on 06.12.2017, 00:00 by Ashley ChonkaAshley Chonka, W Zhou, J Singh, Yang XiangYang 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

01/01/2008

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

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