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Detecting and tracing DDoS attacks by intelligent decision prototype

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conference contribution
posted on 2008-01-01, 00:00 authored by Ashley Chonka, Wanlei 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 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.

History

Event

IEEE International Conference on Pervasive Computing and Communications (6th : 2008 : Hong Kong)

Pagination

578 - 583

Publisher

IEEE

Location

Hong Kong

Place of publication

Piscataway, N.J.

Start date

2008-03-17

End date

2008-03-21

ISBN-10

076953113X

Language

eng

Publication classification

E1 Full written paper - refereed

Copyright notice

2008, IEEE

Title of proceedings

Proceedings of the 6th Annual IEEE International Conference on Pervasive Computing and Communications