Machine learning-based malicious user detection for reliable cooperative radio spectrum sensing in Cognitive Radio-Internet of Things
نویسندگان
چکیده
منابع مشابه
User Selection Based Cooperative Spectrum Sensing for Cognitive Radio Networks
In cooperative spectrum sensing, information from several cognitive users is used for detection of the primary user. To reduce sensing overhead and total energy consumption, it is recommended that users with good performance be selected so as to optimize the probability of detection. One method of selecting the cognitive users with the best detection performance is proposed in this paper. It fo...
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Cognitive Radio is an modern technology that is used to get the picture of spectrum and cope themselves to operate the secondary users who are unlicensed to share the spectrum with licensed primary users. Cooperative spectrum sensing allows unlicensed access whenever possible to the unexploited portions of the licensed spectrum by exploiting the spatial diversity among multiple secondary users....
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Collaborative Spectrum Sensing (CSS) is an effective approach to improve the detection performance in Cognitive Radio (CR) networks. Inherent characteristics of the CR have imposed some additional security threats to the networks. One of the common threats is Primary User Emulation Attack (PUEA). In PUEA, some malicious users try to imitate primary signal characteristics and defraud the CR user...
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Cognitive radio arises as a hot research issue in wireless communications recently, attributed to its capability of enhancing spectral efficiency and catering for the growing demand for bandwidth. As a good embodiment of cognitive radio’s unique feature, i.e. making use of every bit spectral resource, spectrum sensing plays a vital role in the implementation of cognitive radio. To alleviate neg...
متن کاملA Fast Malicious User Detection Scheme Based on POMDP for Cooperative Spectrum Sensing in Cognitive Radio networks
Cooperative spectrum sensing (CSS) can improve spectrum sensing accuracy, but it can be injured due to potential attacks from malicious cognitive radio user who reports false sensing results to the fusion center (FC). Many researchers focus on reducing the effect of malicious users on the accuracy of spectrum sensing. A promising method to detect malicious users is to determine their abnormal s...
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ژورنال
عنوان ژورنال: Machine Learning with Applications
سال: 2021
ISSN: 2666-8270
DOI: 10.1016/j.mlwa.2021.100052