A Novel Approach to Detect Malicious User Node by Cognition in Heterogeneous Wireless Networks

A Novel Approach to Detect Malicious User Node by Cognition in Heterogeneous Wireless Networks

G Sunilkumar

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Thriveni J

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K R Venugopal

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L M Patnaik

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Bangalore University

A Novel Approach to Detect Malicious User Node by Cognition in Heterogeneous Wireless Networks

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Abstract

Cognitive Networks are characterized by their intelligence and adaptability. Securing layered heterogeneous network architectures has always posed a major challenge to researchers. In this paper, the Observe, Orient, Decide and Act (OODA) loop is adopted to achieve cognition. Intelligence is incorporated by the use of discrete time dynamic neural networks. The use of dynamic neural networks is considered, to monitor the instantaneous changes that occur in heterogeneous network environments when compared to static neural networks. Malicious user node identification is achieved by monitoring the service request rates generated to the cognitive servers. The results and the experimental study presented in this paper prove the improved efficiency in terms of malicious node detection and malicious transaction classification when compared to the existing systems.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

G Sunilkumar. 2014. \u201cA Novel Approach to Detect Malicious User Node by Cognition in Heterogeneous Wireless Networks\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 14 (GJCST Volume 14 Issue E2): .

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GJCST Volume 14 Issue E2
Pg. 29- 44

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

cognitive networks Dynamic Neural Networks malicious node detection Network security OODA

Submission ReceivedDecember 15, 2013
Peer Review Double Blind
Handling Editor
Accepted January 3, 2014
Published January 15, 2014

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v1.2

Issue date

June 1, 2014

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Article Matrices

Total Score: 104

Country: India

Subject: Global Journal of Computer Science and Technology - E: Network, Web & Security

Authors: G Sunilkumar, Thriveni J, K R Venugopal, L M Patnaik (PhD/Dr. count: 0)

View Count (all-time): 298

Total Views (Real + Logic): 8944

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Publish Date: 2014 06, Sun

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Total Views: 8944

Total Downloads: 2346

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