2020
DOI: 10.1109/access.2019.2963512
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Clustering Algorithm-Based Data Fusion Scheme for Robust Cooperative Spectrum Sensing

Abstract: In a centralized cooperative spectrum sensing (CSS) system, it is vulnerable to malicious users (MUs) sending fraudulent sensing data, which can severely degrade the performance of CSS system. To solve this problem, we propose sensing data fusion schemes based on K-medoids and Mean-shift clustering algorithms to resist the MUs sending fraudulent sensing data in this paper. The cognitive users (CUs) send their local energy vector (EVs) to the fusion center which fuses these EVs as an EV with robustness by the p… Show more

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Cited by 29 publications
(20 citation statements)
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“…The efficacy of the program, better for hospital decision-making management, medical, scientific research, and teaching services, has become a very important research topic. Rough sets are widely used, including a variety of logical, mathematical, and philosophical aspects of rough sets [ 17 , 18 ]. Rough sets are also associated with many other methods and are also associated with a very broad hybrid system.…”
Section: Introductionmentioning
confidence: 99%
“…The efficacy of the program, better for hospital decision-making management, medical, scientific research, and teaching services, has become a very important research topic. Rough sets are widely used, including a variety of logical, mathematical, and philosophical aspects of rough sets [ 17 , 18 ]. Rough sets are also associated with many other methods and are also associated with a very broad hybrid system.…”
Section: Introductionmentioning
confidence: 99%
“…Cooperative also can work for wide coverage areas where it offers a reliable answer to the hidden-terminal issue since SUs are apart by a larger distance than the correlated (shadow, fading) distance which this distance makes it unlikely for two SUs to be shadowed instantaneously from the PUs. related works on cooperative cognitive radio sensing among users [39,40] have investigated methods where cooperative detection has exploited all users in the cognitive radio network (CRN). Literature proofed that this scheme vitally enhanced the detection reliability of PU activity.…”
Section: Main Aim and Contributionmentioning
confidence: 99%
“…Although cooperation enhances spectrum-sensing performance, CSS is vulnerable to contamination by spectrum sensing data falsification (SSDF) attackers [8][9][10][11] , also known as malicious secondary users (MSUs). They degrade the performance of CSS by reporting falsified sensing results [12] .…”
Section: Introductionmentioning
confidence: 99%