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A Collaborative Approach for Monitoring Nodes Behavior during Spectrum Sensing to Mitigate Multiple Attacks in Cognitive Radio Networks

Title:

A Collaborative Approach for Monitoring Nodes Behavior during Spectrum Sensing to Mitigate Multiple Attacks in Cognitive Radio Networks

Khasawneh, Mahmoud and Agarwal, Anjali (2017) A Collaborative Approach for Monitoring Nodes Behavior during Spectrum Sensing to Mitigate Multiple Attacks in Cognitive Radio Networks. Security and Communication Networks, 2017 . pp. 1-16. ISSN 1939-0114

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Official URL: http://dx.doi.org/10.1155/2017/3261058

Abstract

Spectrum sensing is the first step to overcome the spectrum scarcity problem in Cognitive Radio Networks (CRNs) wherein all unutilized subbands in the radio environment are explored for better spectrum utilization. Adversary nodes can threaten these spectrum sensing results by launching passive and active attacks that prevent legitimate nodes from using the spectrum efficiently. Securing the spectrum sensing process has become an important issue in CRNs in order to ensure reliable and secure spectrum sensing and fair management of resources. In this paper, a novel collaborative approach during spectrum sensing process is proposed. It monitors the behavior of sensing nodes and identifies the malicious and misbehaving sensing nodes. The proposed approach measures the node’s sensing reliability using a value called belief level. All the sensing nodes are grouped into a specific number of clusters. In each cluster, a sensing node is selected as a cluster head that is responsible for collecting sensing-reputation reports from different cognitive nodes about each node in the same cluster. The cluster head analyzes information to monitor and judge the nodes’ behavior. By simulating the proposed approach, we showed its importance and its efficiency for achieving better spectrum security by mitigating multiple passive and active attacks.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Article
Refereed:Yes
Authors:Khasawneh, Mahmoud and Agarwal, Anjali
Journal or Publication:Security and Communication Networks
Date:2017
Funders:
  • Concordia Open Access Author Fund
Digital Object Identifier (DOI):10.1155/2017/3261058
ID Code:983211
Deposited By: DANIELLE DENNIE
Deposited On:14 Nov 2017 15:33
Last Modified:18 Jan 2018 17:56

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