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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.
G Sunilkumar. 2014. "A Novel Approach to Detect Malicious User Node by Cognition in Heterogeneous Wireless Networks". Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 14 (GJCST Volume 14 Issue E2).
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
v1.2
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Total Score: 144
Country: India
Subject: Global Journal of Computer Science and Technology
Authors: G Sunilkumar, Thriveni J, K R Venugopal, L M Patnaik (PhD/Dr. count: 0)
View Count (all-time): 427
Total Views (Real + Logic): 3501
Total Downloads (simulated): 312
Publish Date: 2014 01, Wed
Monthly Totals (Real + Logic):
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