Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/105333
Title: A sequence number prediction based bait detection scheme to mitigate sequence number attacks in MANETs
Authors: Jhaveri, Rutvij H.
Desai, Aneri
Patel, Ankit
Zhong, Yubin
Keywords: Mobile Security
Mobile Ad Hoc Networks
DRNTU::Engineering::Computer science and engineering
Issue Date: 2018
Source: Jhaveri, R. H., Desai, A., Patel, A., & Zhong, Y. (2018). A sequence number prediction based bait detection scheme to mitigate sequence number attacks in MANETs. Security and Communication Networks, 20181-13. doi:10.1155/2018/3210207
Series/Report no.: Security and Communication Networks
Abstract: The characteristics of MANET such as decentralized architecture, dynamic topologies make MANETs susceptible to various security attacks. Sequence number attacks are such type of security threats which tend to degrade the network functioning and performance by sending fabricated route reply packets (RREP) with the objective of getting involved in the route and drop some or all of the data packets during the data transmission phase.The sequence number adversary attempts to send a fabricated high destination number in the RREP packet which attracts the sender to establish a path through the adversary node. This paper proposes a proactive secure routing mechanism which is an improvement over the authors previously proposed scheme. It makes use of linear regression mechanism to predict the maximum destination sequence number that the neighboring node can insert in the RREP packet. As an additional security checkpoint, it uses a bait detection mechanism to establish confidence in marking a suspicious node as a malicious node.The proposed approach works in collaboration with the ad hoc on-demand distance vector routing (AODV) protocol. The simulation results depict that the approach improves the network performance in the presence of adversaries as compared to previously proposed scheme.
URI: https://hdl.handle.net/10356/105333
http://hdl.handle.net/10220/48081
ISSN: 1939-0114
DOI: 10.1155/2018/3210207
Rights: © 2018 Rutvij H. Jhaveri et al.This is an open access article distributed under theCreativeCommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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