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Reseach Article

A Probabilistic Approach to Detect Selfish Node in MANET

Published on January 2014 by Suman Goswami, Saptarshi Das
National Conference on Future Computing 2014
Foundation of Computer Science USA
NCFC2014 - Number 1
January 2014
Authors: Suman Goswami, Saptarshi Das
32793ab1-ff95-473b-81b7-4cb9b1c2f2c3

Suman Goswami, Saptarshi Das . A Probabilistic Approach to Detect Selfish Node in MANET. National Conference on Future Computing 2014. NCFC2014, 1 (January 2014), 23-26.

@article{
author = { Suman Goswami, Saptarshi Das },
title = { A Probabilistic Approach to Detect Selfish Node in MANET },
journal = { National Conference on Future Computing 2014 },
issue_date = { January 2014 },
volume = { NCFC2014 },
number = { 1 },
month = { January },
year = { 2014 },
issn = 0975-8887,
pages = { 23-26 },
numpages = 4,
url = { /proceedings/ncfc2014/number1/14792-1406/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Future Computing 2014
%A Suman Goswami
%A Saptarshi Das
%T A Probabilistic Approach to Detect Selfish Node in MANET
%J National Conference on Future Computing 2014
%@ 0975-8887
%V NCFC2014
%N 1
%P 23-26
%D 2014
%I International Journal of Computer Applications
Abstract

A mobile ad hoc network, literally means a wireless link, which is ad-hoc by nature between several mobile nodes or devices. Each device in a MANET can move freely in any direction, and will therefore change its links to other devices easily. The main challenge in building a MANET is in terms of security. In this paper we are presenting a probabilistic approach to detect selfish nodes using the probability density function. The proposed model works with existing routing protocol and the nodes that are suspected of having the selfishness are given a Selfishness test. This model formulates this problem with the help of prior probability and continuous Bayes' theorem.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Probabilistic Approach