Packet faking attack: a novel attack and detection mechanism in OppNets

Alajeely, Majeed, Ahmad, Asma'a, Doss, Robin and Mak-Hau, Vicky 2014, Packet faking attack: a novel attack and detection mechanism in OppNets, in CIS 2014 : Proceedings of the 10th International Conference on Computational Intelligence and Security, IEEE, Piscataway, N.J., pp. 638-642.

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Title Packet faking attack: a novel attack and detection mechanism in OppNets
Author(s) Alajeely, Majeed
Ahmad, Asma'a
Doss, RobinORCID iD for Doss, Robin orcid.org/0000-0001-6143-6850
Mak-Hau, VickyORCID iD for Mak-Hau, Vicky orcid.org/0000-0002-9306-5780
Conference name Computational Intelligence and Security. Conference (10th: 2014 : Kunming, China)
Conference location Kunming, China
Conference dates 2014/11/15 - 2014/11/16
Title of proceedings CIS 2014 : Proceedings of the 10th International Conference on Computational Intelligence and Security
Editor(s) [Unknown]
Publication date 2014
Conference series Computational Intelligence and Security Conference
Start page 638
End page 642
Total pages 5
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) Denial-of-service
Malicious node detection
Opportunistic networks
Packet dropping attacks
Security
Summary  Security is a major challenge in Opportunistic Networks (OppNets) due to its characteristics of being an open medium with dynamic topology, there is neither a centralized management nor clear lines of defence. A packet dropping attack is one of the major security threats in OppNets as neither source nodes nor destination nodes have any knowledge of when or where a packet will be dropped. In this paper, we present a novel attack and detection mechanism against a special type of packet dropping where the malicious node drops one packet or more and injects a new fake packet instead. Our novel detection mechanism is very powerful and has very high accuracy. It relies on a very simple yet powerful idea; the creation time of each packet. Significant results show this robust mechanism achieves a very high accuracy and detection rate.
Language eng
Field of Research 080303 Computer System Security
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2014, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30070305

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