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Reseach Article

Fuzzy Logic Based Intrusion Detection System against Blackhole Attack on AODV in MANET

Published on December 2011 by Kulbhushan, Jagpreet Singh
Network Security and Cryptography
Foundation of Computer Science USA
NSC - Number 2
December 2011
Authors: Kulbhushan, Jagpreet Singh

Kulbhushan, Jagpreet Singh . Fuzzy Logic Based Intrusion Detection System against Blackhole Attack on AODV in MANET. Network Security and Cryptography. NSC, 2 (December 2011), 28-35.

author = { Kulbhushan, Jagpreet Singh },
title = { Fuzzy Logic Based Intrusion Detection System against Blackhole Attack on AODV in MANET },
journal = { Network Security and Cryptography },
issue_date = { December 2011 },
volume = { NSC },
number = { 2 },
month = { December },
year = { 2011 },
issn = 0975-8887,
pages = { 28-35 },
numpages = 8,
url = { /specialissues/nsc/number2/4331-spe024t/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Special Issue Article
%1 Network Security and Cryptography
%A Kulbhushan
%A Jagpreet Singh
%T Fuzzy Logic Based Intrusion Detection System against Blackhole Attack on AODV in MANET
%J Network Security and Cryptography
%@ 0975-8887
%N 2
%P 28-35
%D 2011
%I International Journal of Computer Applications

Security[16] is an essential feature for wired and wireless network[1]. But due to its unique characteristics of MANETs[10], it creates a number of consequential security challenges to network. MANETs are vulnerable to various attacks[2], blackhole[12] is one of the possible attack. In this paper, we represent an intrusion detection[5] system for MANETs against blackhole attack using fuzzy logic[4]. Our system successfully detects the blackhole in the network and this information is passed to other nodes also. We also provide a detailed performance evaluation based on various network parameters. Our results show that the proposed system not only detects the blackhole[12] node, but improves the performance of AODV under the blackhole attack.

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Index Terms

Computer Science
Information Sciences


MANET Blackhole Attack Fuzzy Logic