A sequential cooperative spectrum sensing scheme based on cognitive user reputation

Vu-Van, Hiep; Koo, Insoo

doi:10.1109/tce.2012.6414979

Cited by 28 publications

(10 citation statements)

References 13 publications

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“…The spectrum sensing operation of each SU in a particular spectrum results in deciding hypotheses H 1 and H 0 as [18,32,39] …”

Section: System Modelmentioning

confidence: 99%

“…According to the central limit theorem (CLT), if the number of samples is large enough, Z j i is asymptotically normally distributed under both H 0 and H 1 hypotheses [18,32] as…”

Section: System Modelmentioning

confidence: 99%

“…CSS is investigated as an efficient detection method in the presence of primary user emulation attack in [16]. Priority values are assigned to SUs based on reputation results of each SU in [17][18][19][20] to give less importance to the sensing results of SUs with a reputation below threshold. A reputation-based CSS method is proposed in [21] that improves the system performance by detecting and rejecting the Byzantine malicious users, in order to improve system performance and efficiency.…”

Section: Introductionmentioning

confidence: 99%

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Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm

Gul

Qureshi

Elahi

et al. 2018

International Journal of Antennas and Propagation

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In cognitive radio network (CRN), secondary users (SUs) try to sense and utilize the vacant spectrum of the legitimate primary user (PU) in an efficient manner. The process of cooperation among SUs makes the sensing more authentic with minimum disturbance to the PU in achieving maximum utilization of the vacant spectrum. One problem in cooperative spectrum sensing (CSS) is the occurrence of malicious users (MUs) sending false data to the fusion center (FC). In this paper, the FC takes a global decision based on the hard binary decisions received from all SUs. Genetic algorithm (GA) using one-to-many neighbor distance along with z-score as a fitness function is used for the identification of accurate sensing information in the presence of MUs. The proposed scheme is able to avoid the effect of MUs in CSS without identification of MUs. Four types of abnormal SUs, opposite malicious user (OMU), random opposite malicious user (ROMU), always yes malicious user (AYMU), and always no malicious user (ANMU), are discussed in this paper. Simulation results show that the proposed hard fusion scheme has surpassed the existing hard fusion scheme, equal gain combination (EGC), and maximum gain combination (MGC) schemes by employing GA.

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“…The spectrum sensing operation of each SU in a particular spectrum results in deciding hypotheses H 1 and H 0 as [18,32,39] …”

Section: System Modelmentioning

confidence: 99%

“…According to the central limit theorem (CLT), if the number of samples is large enough, Z j i is asymptotically normally distributed under both H 0 and H 1 hypotheses [18,32] as…”

Section: System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm

Gul

Qureshi

Elahi

et al. 2018

International Journal of Antennas and Propagation

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“…In [19] is proposed a channel quality-based activation rule that chooses some SUs to be active during the sensing and report phases. In [20,21], a sequential cooperative spectrum sensing (SCSS) scheme is explored. In SCSS, the FC coordinates the report of local decisions in the secondary network, choosing the SUs that report their local sensing information.…”

Section: Introductionmentioning

confidence: 99%

Combined Pre-Distortion and Censoring for Bandwidth-Efficient and Energy-Efficient Fusion of Spectrum Sensing Information

Aquino

Guimarães

Mendes

et al. 2017

Sensors

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This paper describes a novel scheme for the fusion of spectrum sensing information in cooperative spectrum sensing for cognitive radio applications. The scheme combines a spectrum-efficient, pre-distortion-based fusion strategy with an energy-efficient censoring-based fusion strategy to achieve the combined effect of reduction in bandwidth and power consumption during the transmissions of the local decisions to the fusion center. Expressions for computing the key performance metrics of the spectrum sensing of the proposed scheme are derived and validated by means of computer simulations. An extensive analysis of the overall energy efficiency is made, along with comparisons with reference strategies proposed in the literature. It is demonstrated that the proposed fusion scheme can outperform the energy efficiency attained by these reference strategies. Moreover, it attains approximately the same global decision performance of the best among these strategies.

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“…A variety of approaches have been proposed in the literature [13][14][15] to restrict malicious users in different applications. In [15], the authors proposed an encrypted identification tag for the authentication of CUs and a reliability test for the detection of unreliable and malicious users.…”

mentioning

confidence: 99%

Secure Cooperative Spectrum Sensing via a Novel User-Classification Scheme in Cognitive Radios for Future Communication Technologies

Usman¹,

Koo²

2015

Symmetry

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Future communication networks would be required to deliver data on a far greater scale than is known to us today, thus mandating the maximal utilization of the available radio spectrum using cognitive radios. In this paper, we have proposed a novel cooperative spectrum sensing approach for cognitive radios. In cooperative spectrum sensing, the fusion center relies on reports of the cognitive users to make a global decision. The global decision is obtained by assigning weights to the reports received from cognitive users. Computation of such weights requires prior information of the probability of detection and the probability of false alarms, which are not readily available in real scenarios. Further, the cognitive users are divided into reliable and unreliable categories based on their weighted energy by using some empirical threshold. In this paper, we propose a method to classify the cognitive users into reliable, neutral and unreliable categories without using any pre-defined or empirically-obtained threshold. Moreover, the computation of weights does not require the detection, or false alarm probabilities, or an estimate of these probabilities. Reliable cognitive users are assigned the highest weights; neutral cognitive users are assigned medium weights (less than the reliable and higher than the unreliable cognitive users' weights); and unreliable users are assigned the least weights. We show the performance improvement of our proposed method through simulations by comparing it with the conventional cooperative spectrum sensing scheme through different metrics, like receiver operating characteristic (ROC) curve and OPEN ACCESSSymmetry 2015, 7 676 mean square error. For clarity, we also show the effect of malicious users on detection probability and false alarm probability individually through simulations.

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A sequential cooperative spectrum sensing scheme based on cognitive user reputation

Cited by 28 publications

References 13 publications

Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm

Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm

Combined Pre-Distortion and Censoring for Bandwidth-Efficient and Energy-Efficient Fusion of Spectrum Sensing Information

Secure Cooperative Spectrum Sensing via a Novel User-Classification Scheme in Cognitive Radios for Future Communication Technologies

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