A sequence number prediction based bait detection scheme to mitigate sequence number attacks in MANETs
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 (...
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sg-ntu-dr.10356-1053332019-12-06T21:49:18Z A sequence number prediction based bait detection scheme to mitigate sequence number attacks in MANETs Jhaveri, Rutvij H. Desai, Aneri Patel, Ankit Zhong, Yubin School of Electrical and Electronic Engineering Delta-NTU Corporate Laboratory Mobile Security Mobile Ad Hoc Networks DRNTU::Engineering::Computer science and engineering 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. Published version 2019-04-26T06:14:14Z 2019-12-06T21:49:18Z 2019-04-26T06:14:14Z 2019-12-06T21:49:18Z 2018 2018 Journal Article 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 1939-0114 https://hdl.handle.net/10356/105333 http://hdl.handle.net/10220/48081 https://doi.org/10.1155/2018/3210207 209920 en Security and Communication Networks © 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. 14 p. application/pdf |
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Mobile Security Mobile Ad Hoc Networks DRNTU::Engineering::Computer science and engineering Jhaveri, Rutvij H. Desai, Aneri Patel, Ankit Zhong, Yubin A sequence number prediction based bait detection scheme to mitigate sequence number attacks in MANETs |
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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. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Jhaveri, Rutvij H. Desai, Aneri Patel, Ankit Zhong, Yubin |
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Article |
author |
Jhaveri, Rutvij H. Desai, Aneri Patel, Ankit Zhong, Yubin |
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Jhaveri, Rutvij H. |
title |
A sequence number prediction based bait detection scheme to mitigate sequence number attacks in MANETs |
title_short |
A sequence number prediction based bait detection scheme to mitigate sequence number attacks in MANETs |
title_full |
A sequence number prediction based bait detection scheme to mitigate sequence number attacks in MANETs |
title_fullStr |
A sequence number prediction based bait detection scheme to mitigate sequence number attacks in MANETs |
title_full_unstemmed |
A sequence number prediction based bait detection scheme to mitigate sequence number attacks in MANETs |
title_sort |
sequence number prediction based bait detection scheme to mitigate sequence number attacks in manets |
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2019 |
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https://hdl.handle.net/10356/105333 http://hdl.handle.net/10220/48081 https://doi.org/10.1155/2018/3210207 |
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1681042706280742912 |