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Reseach Article

Detecting Packet Dropping Misbehaving Nodes using Support Vector Machine (SVM) in MANET

by Nirav J. Patel, Rutvij H. Jhaveri
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 4
Year of Publication: 2015
Authors: Nirav J. Patel, Rutvij H. Jhaveri
10.5120/21689-4794

Nirav J. Patel, Rutvij H. Jhaveri . Detecting Packet Dropping Misbehaving Nodes using Support Vector Machine (SVM) in MANET. International Journal of Computer Applications. 122, 4 ( July 2015), 26-32. DOI=10.5120/21689-4794

@article{ 10.5120/21689-4794,
author = { Nirav J. Patel, Rutvij H. Jhaveri },
title = { Detecting Packet Dropping Misbehaving Nodes using Support Vector Machine (SVM) in MANET },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 4 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 26-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number4/21689-4794/ },
doi = { 10.5120/21689-4794 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:09:42.516675+05:30
%A Nirav J. Patel
%A Rutvij H. Jhaveri
%T Detecting Packet Dropping Misbehaving Nodes using Support Vector Machine (SVM) in MANET
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 4
%P 26-32
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Mobile ad-hoc network is suffering with various attacks due to the infrastructure-less network. Hence, MANET needs very specific security methods to detect false entrance of the misbehavior nodes. The networks work well if the nodes are trusty and act rightly cooperatively. In this paper, we are identifying and detecting packet dropping nodes using Support vector machine. Support vector machine is used reactively to classify nodes in two different classes either normal or malicious nodes. SVM takes as input the neighbor trust value, calculated with data packets and control packets. Our technique is implemented with AODV (Ad-hoc on demand vector routing) protocol. Our experimental results evaluated using packet delivery ratio (PDR), End-To-End delay, Average throughput, Normalized Routing Overhead, Average Energy Consumption.

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Index Terms

Computer Science
Information Sciences

Keywords

Mobile ad hoc network machine learning techniques packet dropping attacks support vector machine (SVM)