Cognitive radio network as wireless sensor network (II): Security consideration

Lin, Feng; Hu, Zhen; Hou, Shujie; Yu, Jingzhi; Zhang, Changchun; Guo, Nan; Wicks, Michael C.; Qiu, Robert C.; Currie, Kenneth R.

doi:10.1109/naecon.2011.6183125

Cited by 24 publications

(15 citation statements)

References 14 publications

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“…In summary, the work in this paper generalizes those in [7], [8], by incorporating inaccurate location measurements, noisy sensor reports, and time-varying PU and malicious user activity. As with earlier approaches, the work in this paper can always be combined with a trust-based reputation management system that can track and black-list malicious SUs [16].…”

Section: A Related Workmentioning

confidence: 93%

“…A unified approach presented in [8] combines similar ideas and performs joint spectrum sensing and outlier identification by exploiting network topology, node locations, and signal propagation characteristics. Further extensions of this idea are provided in [7], where a robust version of principal component analysis (PCA) is utilized to jointly estimate the PU powers and outlier locations.…”

Section: A Related Workmentioning

confidence: 99%

“…Existing works have proposed the use of node location information for spectrum sensing and attack avoidance [7]. The present paper proposes a generalized robust CSS framework that not only identifies malicious users and spectrum opportunities, but also handles inaccurate or missing distance measurements and noisy SU reports.…”

Section: Introductionmentioning

confidence: 99%

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Outlier-aware spectrum sensing in cognitive radio networks

Kapoor

Rajawat

2014

2014 8th International Conference on Signal Processing and Communication Systems (ICSPCS)

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This paper considers the problem of cooperative spectrum sensing in cognitive radio networks (CRN). Communication in CRNs may be disrupted due to the presence of malicious secondary users (SU) or channel impairments such as shadowing. This paper proposes a spatio-frequency framework that can detect and track malicious users and anomalous measurements in CRNs. The joint problem of spectrum sensing and malicious user identification is posed as an optimization problem that aims to exploit the sparsity inherent to both, spectrum occupancy and malicious user occurrence. Proposed scheme obtains improved performance by utilizing node location information, and can handle missing or inaccurate location information, and noisy SU reports. A distributed block-coordinate descent-based algorithm is proposed, that outperforms the state-of-the-art PCA-based approach, and is flexible enough to defeat a variety of attacks encountered in SU networks. Simulation results demonstrate the efficacy of the proposed algorithm.

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Section: A Related Workmentioning

confidence: 93%

Section: A Related Workmentioning

confidence: 99%

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Outlier-aware spectrum sensing in cognitive radio networks

Kapoor

Rajawat

2014

2014 8th International Conference on Signal Processing and Communication Systems (ICSPCS)

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“…The following research work addresses the active PUEA. In [23], a robust technique for spectrum sensing process is proposed based on the principal component analysis to find any attack targeting the network. A detection method of PUEA is proposed in [24].…”

Section: Related Workmentioning

confidence: 99%

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

Khasawneh

Agarwal

2017

Security and Communication Networks

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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.

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“…Therefore, CR provides a resolution to spectrum inefficiency and the shortage on these bands by allowing CR users (secondary users (SUs)) to opportunistically access vacant spectrum space [6]. This results in providing great opportunities for a rising number of SUs to use these bands through an optimised approach for utilising radio resources [7][8].…”

Section: Introductionmentioning

confidence: 99%

Spectrum Sharing Security and Attacks in CRNs: a Review

Alhakami¹,

Mansour²,

Safdar³

2014

IJACSA

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Abstract-Cognitive Radio plays a major part in communication technology by resolving the shortage of the spectrum through usage of dynamic spectrum access and artificial intelligence characteristics. The element of spectrum sharing in cognitive radio is a fundamental approach in utilising free channels. Cooperatively communicating cognitive radio devices use the common control channel of the cognitive radio medium access control to achieve spectrum sharing. Thus, the common control channel and consequently spectrum sharing security are vital to ensuring security in the subsequent data communication among cognitive radio nodes. In addition to well known security problems in wireless networks, cognitive radio networks introduce new classes of security threats and challenges, such as licensed user emulation attacks in spectrum sensing and misbehaviours in the common control channel transactions, which degrade the overall network operation and performance. This review paper briefly presents the known threats and attacks in wireless networks before it looks into the concept of cognitive radio and its main functionality. The paper then mainly focuses on spectrum sharing security and its related challenges. Since spectrum sharing is enabled through usage of the common control channel, more attention is paid to the security of the common control channel by looking into its security threats as well as protection and detection mechanisms. Finally, the pros and cons as well as the comparisons of different CR-specific security mechanisms are presented with some open research issues and challenges.

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Cognitive radio network as wireless sensor network (II): Security consideration

Cited by 24 publications

References 14 publications

Outlier-aware spectrum sensing in cognitive radio networks

Outlier-aware spectrum sensing in cognitive radio networks

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

Spectrum Sharing Security and Attacks in CRNs: a Review

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