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Reinforcement based Cognitive Algorithms to Detect Malicious Node in Wireless Networks

by G Sunilkumar, Thriveni J, K R Venugopal, Manjunatha C, L M Patnaik
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 109 - Number 16
Year of Publication: 2015
Authors: G Sunilkumar, Thriveni J, K R Venugopal, Manjunatha C, L M Patnaik
10.5120/19273-0990

G Sunilkumar, Thriveni J, K R Venugopal, Manjunatha C, L M Patnaik . Reinforcement based Cognitive Algorithms to Detect Malicious Node in Wireless Networks. International Journal of Computer Applications. 109, 16 ( January 2015), 29-34. DOI=10.5120/19273-0990

@article{ 10.5120/19273-0990,
author = { G Sunilkumar, Thriveni J, K R Venugopal, Manjunatha C, L M Patnaik },
title = { Reinforcement based Cognitive Algorithms to Detect Malicious Node in Wireless Networks },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 109 },
number = { 16 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 29-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume109/number16/19273-0990/ },
doi = { 10.5120/19273-0990 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:44:58.025028+05:30
%A G Sunilkumar
%A Thriveni J
%A K R Venugopal
%A Manjunatha C
%A L M Patnaik
%T Reinforcement based Cognitive Algorithms to Detect Malicious Node in Wireless Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 109
%N 16
%P 29-34
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The growth of wireless communication technologies and its applications leads to many security issues. Malicious node detection is one among the major security issues. Adoption of cognition can detect and Prevent malicious activities in the wireless networks. To achieve cognition into wireless networks, we are using reinforcement learning techniques. By using the existing reinforcement techniques, we have proposed GreedyQ cognitive (GQC) and SoftSARSA cognitive (SSC) algorithms for malicious node detection and the performances among these algorithms are evaluated and the result shows SSC algorithm is best algorithm. The proposed algorithms perform better in malicious node detection as compared to the existing algorithms.

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Index Terms

Computer Science
Information Sciences

Keywords

Malicious node detection Reinforcement learning algorithm Cognition Wireless networks.