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16-09-2022

FSSAM: A Five Stage Security Analysis Model for Detecting and Preventing Wormhole Attack in Mobile Ad-Hoc Networks Using Adaptive Atom Search Algorithm

Authors: D. Hemanand, N. Sankar Ram, D. S. Jayalakshmi

Published in: Wireless Personal Communications

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Abstract

Mobile Ad-hoc Network is a decentralized wireless network which is drastically growing day by day. It can be vulnerable to several threats and attacks, namely wormhole attacks, due to some characteristics, such as node, location, time etc.; hence it leads to loss of data, route failure, and data route diversion. Moreover, several existing approaches have been introduced to resolve the wormhole attack, yet suffering from higher consumed energy, high delay in packet delivery and less throughput. A Five Stage Security Analysis Model is developed to effectively detect and prevent the wormhole attack by considering these problems. The five-stage model investigates the information like route, node location, time, hop count and neighbour analysis in the network. The proposed model cannot need any middleware or some special type of hardware, and also it minimizes the energy and delay by keeping away from executing wormhole detection for every node present in the network. The Network Simulator-2 software is used to provide the simulation of the proposed model FSSAM. The performance is evaluated, and simulation results are verified in terms of throughput, delay, energy, packet loss, end-to-end delay and packet delivery ratio. The determined outcomes have proved that the proposed model performed better for wormhole detection and prevention than existing approaches.
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Metadata
Title
FSSAM: A Five Stage Security Analysis Model for Detecting and Preventing Wormhole Attack in Mobile Ad-Hoc Networks Using Adaptive Atom Search Algorithm
Authors
D. Hemanand
N. Sankar Ram
D. S. Jayalakshmi
Publication date
16-09-2022
Publisher
Springer US
Published in
Wireless Personal Communications
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-022-09964-9