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Malicious node traceback in opportunistic networks using merkle trees
conference contribution
posted on 2015-12-14, 00:00 authored by Majeed AlajeelyMajeed Alajeely, Asma'a Ahmad, Robin Ram Mohan DossRobin Ram Mohan DossSecurity is a major challenge in Opportunistic Networks because of its characteristics, such as open medium, dynamic topology, no centralized management and absent clear lines of defense. A packet dropping attack is one of the major security threats in OppNets since neither source nodes nor destination nodes have the knowledge of where or when the packet will be dropped. In this paper, we present a malicious nodes detection mechanism against a special type of packet dropping attack where the malicious node drops one or more packets and then injects new fake packets instead. Our novel detection and traceback mechanism is very powerful and has very high accuracy. Each node can detect and then traceback the malicious nodes based on a solid and powerful idea that is, Merkle tree hashing technique. In our defense techniques we have two stages. The first stage is to detect the attack, and the second stage is to find the malicious nodes. We have compared our approach with the acknowledgement based mechanisms and the networks coding based mechanism which are well known approaches in the literature. Simulation results show this robust mechanism achieves a very high accuracy and detection rate.
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Event
IEEE International Conference on Data Science and Data Intensive Systems (2015 : Sydney, New South Wales)Pagination
147 - 152Publisher
IEEELocation
Sydney, New South WalesPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2015-12-11End date
2015-12-13ISBN-13
9781509002146Language
EngPublication classification
E Conference publication; E1 Full written paper - refereedCopyright notice
2015, IEEEEditor/Contributor(s)
J Chen, L YangTitle of proceedings
DSDIS 2015: Proceedings of the IEEE International Conference on Data Science and Data Intensive SystemsUsage metrics
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