Robust Collaborative Spectrum Sensing Schemes for Cognitive Radio Networks

Li, Hongjuan; Cheng, Xiuzhen; Li, Keqiu; Hu, Chunqiang; Zhang, Nan; Xue, Weilian

doi:10.1109/tpds.2013.73

Cited by 34 publications

(17 citation statements)

References 24 publications

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“…Li et al have shown the performance comparison of their algorithms with that of SCST under different malicious ratios in [12]. We compare the performance of our proposed algorithm with that of SCST by varying the malicious user ratio, network scale, rank order and compression ratio.…”

Section: B Sensing Decisionsmentioning

confidence: 99%

Low-rank matrix completion based malicious user detection in cooperative spectrum sensing

Qin

Gao

Plumbley

et al. 2013

2013 IEEE Global Conference on Signal and Information Processing

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Abstract-In a cognitive radio (CR) system, cooperative spectrum sensing (CSS) is the key to improving sensing performance in deep fading channels. In CSS networks, signals received at the secondary users (SUs) are sent to a fusion center to make a final decision of the spectrum occupancy. In this process, the presence of malicious users sending false sensing samples can severely degrade the performance of the CSS network. In this paper, with the compressive sensing (CS) technique being implemented at each SU, we build a CSS network with double sparsity property. A new malicious user detection scheme is proposed by utilizing the adaptive outlier pursuit (AOP) based low-rank matrix completion in the CSS network. In the proposed scheme, the malicious users are removed in the process of signal recovery at the fusion center. The numerical analysis of the proposed scheme is carried out and compared with an existing malicious user detection algorithm.

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Section: B Sensing Decisionsmentioning

confidence: 99%

Low-rank matrix completion based malicious user detection in cooperative spectrum sensing

Qin

Gao

Plumbley

et al. 2013

2013 IEEE Global Conference on Signal and Information Processing

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“…2. Data injection attack [17,18,28] We take into consideration a second type of attack where the malicious users send falsified sensing reports to fool the FC. In fact, a malicious user may:…”

Section: Adversary Modelmentioning

confidence: 99%

“…This process is usually inconvenient and requires significant overhead. In [18], the authors present a new scheme that can calculate a trust value for each secondary user based on a comparison between its sensing report and the reports of its neighborhood. However, the trust value may give wrong results in some realizations of the channels if the neighborhood detected wrong sensing report.…”

Section: Introductionmentioning

confidence: 99%

Location privacy preservation in secure crowdsourcing-based cooperative spectrum sensing

Chkirbene

Hasna

Hamila

et al. 2016

J Wireless Com Network

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Spectrum sensing is one of the most essential components of cognitive radio since it detects whether the spectrum is available or not. However, spectrum sensing accuracy is often degraded due to path loss, interference, and shadowing. Cooperative spectrum sensing (CSS) is one of the proposed solutions to overcome these challenges. It is a key function for dynamic spectrum access that can increase largely the reliability in cognitive radio networks. In fact, several users cooperate to detect the availability of a wireless channel by exploiting spatial diversity. However, cooperative sensing is also facing some series of security threats. In this paper, we focus on two major problems. The first problem is the localization preservation of the secondary users. In fact, malicious users can exploit spatial diversity to localize a secondary user by linking his location-dependent sensing report to his physical position. The existing solutions present a high level of complexity which decreases the performance of the systems. The second problem is the data injection attack, in which malicious CR users may affect the decisions taken by the cognitive users by providing false information, introducing spectrum sensing data falsification (SSDF). In fact, they can submit false sensing reports containing power measurements much larger (or smaller) than the true value to inflate (or deflate) the final average, in which case the fusion center may falsely determine that the channel is busy (or vacant) which increases the false alarm and miss detection probabilities. In this paper, we propose a novel scheme to overcome these problems: iterative per cluster malicious detection (IPCMD). It utilizes applied cryptographic techniques to allow the fusion center (FC) to securely obtain the aggregated result from various secondary users without learning each individual report. IPCMD combines the aggregated sensing reports with their reputation scores during data fusion. The proposed scheme is based on a new algorithm for key generation which can significantly reduce the key management complexity and consequently increase the system performance. Therefore, it can enable secure cooperative spectrum sensing and improve the secondary user location privacy.

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“…Each v∈V S is equipped with q cognitive radios, which are able to detect available data channels [7] [8]. Each SU is also equipped with a traditional wireless interface, which forms a common control channel (CCC) to transmit control messages (such as RREQ in section V).…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

Joint Routing and Channel Assignment for Delay Minimization in Multi-Channel Multi-Flow Mobile Cognitive Ad Hoc Networks

Zhou¹,

Tang²,

Li³

et al. 2014

2015 IEEE Global Communications Conference (GLOBECOM)

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Channel interference and node mobility cause significant performance degradation to wireless networks. In multichannel multi-flow mobile cognitive ad hoc networks, it becomes even worse due to both unexpected primary user activities and potential interference among multiple flows. In this paper, we propose a Joint Routing and Channel Assignment (JRCA) approach based on delay prediction. Firstly, it formulates the JRCA problem with the objective of delay minimization. Next, a delay prediction model is proposed based on the channel collision probability. Then, a heuristic algorithm joints routing and channel assignment is designed to solve the JRCA problem. the JRCA algorithm can find out the path with minimal end-toend (e2e) delay. NS2-based simulation results demonstrate that the JRCA approach significantly outperforms related proposals in terms of average e2e delay.

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Robust Collaborative Spectrum Sensing Schemes for Cognitive Radio Networks

Cited by 34 publications

References 24 publications

Low-rank matrix completion based malicious user detection in cooperative spectrum sensing

Low-rank matrix completion based malicious user detection in cooperative spectrum sensing

Location privacy preservation in secure crowdsourcing-based cooperative spectrum sensing

Joint Routing and Channel Assignment for Delay Minimization in Multi-Channel Multi-Flow Mobile Cognitive Ad Hoc Networks

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