Malicious User Detection in a Cognitive Radio Cooperative Sensing System
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In this article, the authors investigate schemes to identify the malicious users based on outlier detection techniques for a cooperative sensing system employing energy detection at the sensors, considering constraints imposed by the CR scenario such as the lack of information about the primary signal propagation environment and the small size of the sensing data samples.Abstract:
Reliable detection of primary users (PUs) is an important task for cognitive radio (CR) systems. Cooperation among a few spectrum sensors has been shown to offer significant gain in the performance of the CR spectrum-sensing system by countering the shadow-fading effects. We consider a parallel fusion network in which the sensors send their sensing information to an access point which makes the final decision regarding presence or absence of the PU signal. It has been shown in the literature that the presence of malicious users sending false sensing data can severely degrade the performance of such a cooperative sensing system. In this paper, we investigate schemes to identify the malicious users based on outlier detection techniques for a cooperative sensing system employing energy detection at the sensors. We take into consideration constraints imposed by the CR scenario such as the lack of information about the primary signal propagation environment and the small size of the sensing data samples. Considering partial information of the PU activity, we propose a novel method to identify the malicious users. We further propose malicious user detection schemes that take into consideration the spatial information of the CR sensors. The performance of the proposed schemes are studied using simulations.read more
Citations
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When Attackers Meet AI: Learning-Empowered Attacks in Cooperative Spectrum Sensing
TL;DR: Li et al. as discussed by the authors proposed a learning-empowered attack framework named Learning-Evaluation-Beating (LEB) to mislead the fusion center by constructing a surrogate model of the fusion centre's decision model.
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A Multi-factor Trust Management Scheme for Secure Spectrum Sensing in Cognitive Radio Networks
TL;DR: This paper proposes a novel trust management mechanism that evaluates the trustworthiness of each node participating in the CSS scheme called sensing reputation (SR), and introduces the concept of sensing reputation chain to record and track the future behavior of the identified suspicious users.
Journal ArticleDOI
CoPD: a conjugate prior based detection scheme to countermeasure spectrum sensing data falsification attacks in cognitive radio networks
TL;DR: A distributed defense scheme, termed conjugate prior based SSDF detection (CoPD), to countermeasure the SSDF attack, which can effectively exclude the malicious sensing reports from SSDF attackers, so that benign SUs can effectively detect the PU activity.
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Robust collaborative spectrum sensing based on beta reputation system
Kamran Arshad,Klaus Moessner +1 more
TL;DR: A credibility based mechanism for collaborative spectrum sensing using beta reputation system has been introduced and results show that proposed scheme significantly improves the reliability of aggregated data in the presence of falsified users.
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Cognitive Radio Networks: Realistic or Not?
TL;DR: In this article, the authors present a set of real-world scenarios, inspired by realistic settings in commercial telecommunications networks, focusing on spectrum sensing as a basic and critical functionality in the deployment of CRs.
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