2011
DOI: 10.1109/tmc.2010.252
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Secure Cooperative Sensing in IEEE 802.22 WRANs Using Shadow Fading Correlation

Abstract: Abstract-Cooperative (or distributed) sensing has been recognized as a viable means to enhance the incumbent signal detection by exploiting the diversity of sensors. However, it is challenging to secure such distributed sensing due mainly to the unique features of dynamic spectrum access networks-openness of low-layer protocol stacks in software-defined radio devices and the absence of interactions/coordination between primary and secondary devices. To meet this challenge, we propose an attack-tolerant distrib… Show more

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Cited by 70 publications
(40 citation statements)
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“…One is the primary user emulation (PUE) attack [6,18], where an attacker masquerades as the primary transmitter from the vantage point of its neighbors. The other attack is the SSDF [5,13], in which compromised users falsify the local spectrum sensor reports to obscure the existence or create the illusion of a primary signal at the FC [19]. Both of these attacks attempt to deceive the FC on the availability of spectrum resources, causing networks to behave in unintended ways.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…One is the primary user emulation (PUE) attack [6,18], where an attacker masquerades as the primary transmitter from the vantage point of its neighbors. The other attack is the SSDF [5,13], in which compromised users falsify the local spectrum sensor reports to obscure the existence or create the illusion of a primary signal at the FC [19]. Both of these attacks attempt to deceive the FC on the availability of spectrum resources, causing networks to behave in unintended ways.…”
Section: Related Workmentioning
confidence: 99%
“…Secondly, they have no reputation model to go along with anomaly detection, so their solution discards the sensor reports in single intervals instead of penalizing the sensors for an extended duration. In [19,25], the authors developed solutions using RSS estimation models and support vector machines (SVMs), a machine learning technique, to classify sensors as either anomaly or normal. Unlike the various aforementioned solutions, we developed our own defense based on cluster analysis and community detection to safeguard sensor reputations from manipulation, instead of only focusing on the integrity of the CCS.…”
Section: Related Workmentioning
confidence: 99%
“…In the simulation, we consider a representative scenario in which the frequency of WSP a is lower than that of WSP c, i.e., f a ¼ 500 MHz and f c ¼ 1 GHz, and thus, we expect the NE points to be formed such that p à a > p à c . 8 Fig . 8 shows the best responses for WSPs under different SU densities.…”
Section: Existence and Uniqueness Of Nash Equilibriummentioning
confidence: 99%
“…However, licensed users, referred to as primary users (PUs), have been reluctant to share their licensed spectrum because of 1) concerns of interference from (unlicensed) secondary users (SUs) that can lead to potential loss of profit and 2) the lack of attractive incentives for PUs to share their licensed spectrum bands. The fear of interference can be overcome via recent advances in spectrum sensing technologies [5], [6], [7], [8] and proposals for a geolocation database [9], [10]. Thus, in order to realize the potential benefits of DSA, we need to construct effective mechanisms that incentivize the (licensed) spectrum owners to share spectrum resources with SUs.…”
Section: Introductionmentioning
confidence: 99%
“…In [6], the authors propose the expectation maximization (EM) algorithm to determine the channel state and classify the users. In [7], SUs use energy detection and transmit signal strengths that they have sensed to the fusion center (FC). Based on these signal strengths, the FC decides whether the channel is being used by PUs or not.…”
Section: Introductionmentioning
confidence: 99%