Abhishek Kumar, Nitin Gupta, Riya Tapwal, Jagdeep Singh
{"title":"基于信任感知方案的认知无线网络协同频谱感知恶意节点检测","authors":"Abhishek Kumar, Nitin Gupta, Riya Tapwal, Jagdeep Singh","doi":"10.1145/3427477.3429992","DOIUrl":null,"url":null,"abstract":"Emerging of Cognitive Radio (CR) technology has provided an optimistic solution for the dearth of the spectrum by improving the spectrum utilization. The opportunistic use of the spectrum is enabled by spectrum sensing which is one of the key functionality of CR systems. To perform the interference-free transmission in cognitive radio networks, an important part for the unlicensed user is to identify a licensed user with the help of spectrum sensing. Recently, the Cooperative Spectrum Sensing has been widely used in the literature where various scattered unlicensed users collaborate to make the final sensing decision. This overcomes the hidden terminal problem and also improve the overall reliability of the decisions made about the presence or absence of a licensed user. Each unlicensed user sends the sensing results to the base station for the final decision. However, there exist some nodes which do not provide the correct sensing results to maximize their own profit which can highly degrade the CR network functionality. In this paper, a trust-aware model is proposed for the detection of misbehaving nodes such that their sensing reports can be filtered out from the final result. The performance evaluation of the proposed scheme is done by checking its robustness and efficiency against various possible attacks.","PeriodicalId":435827,"journal":{"name":"Adjunct Proceedings of the 2021 International Conference on Distributed Computing and Networking","volume":"129 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Trust Aware Scheme based Malicious Nodes Detection under Cooperative Spectrum Sensing for Cognitive Radio Networks\",\"authors\":\"Abhishek Kumar, Nitin Gupta, Riya Tapwal, Jagdeep Singh\",\"doi\":\"10.1145/3427477.3429992\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Emerging of Cognitive Radio (CR) technology has provided an optimistic solution for the dearth of the spectrum by improving the spectrum utilization. The opportunistic use of the spectrum is enabled by spectrum sensing which is one of the key functionality of CR systems. To perform the interference-free transmission in cognitive radio networks, an important part for the unlicensed user is to identify a licensed user with the help of spectrum sensing. Recently, the Cooperative Spectrum Sensing has been widely used in the literature where various scattered unlicensed users collaborate to make the final sensing decision. This overcomes the hidden terminal problem and also improve the overall reliability of the decisions made about the presence or absence of a licensed user. Each unlicensed user sends the sensing results to the base station for the final decision. However, there exist some nodes which do not provide the correct sensing results to maximize their own profit which can highly degrade the CR network functionality. In this paper, a trust-aware model is proposed for the detection of misbehaving nodes such that their sensing reports can be filtered out from the final result. The performance evaluation of the proposed scheme is done by checking its robustness and efficiency against various possible attacks.\",\"PeriodicalId\":435827,\"journal\":{\"name\":\"Adjunct Proceedings of the 2021 International Conference on Distributed Computing and Networking\",\"volume\":\"129 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Adjunct Proceedings of the 2021 International Conference on Distributed Computing and Networking\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3427477.3429992\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Adjunct Proceedings of the 2021 International Conference on Distributed Computing and Networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3427477.3429992","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Trust Aware Scheme based Malicious Nodes Detection under Cooperative Spectrum Sensing for Cognitive Radio Networks
Emerging of Cognitive Radio (CR) technology has provided an optimistic solution for the dearth of the spectrum by improving the spectrum utilization. The opportunistic use of the spectrum is enabled by spectrum sensing which is one of the key functionality of CR systems. To perform the interference-free transmission in cognitive radio networks, an important part for the unlicensed user is to identify a licensed user with the help of spectrum sensing. Recently, the Cooperative Spectrum Sensing has been widely used in the literature where various scattered unlicensed users collaborate to make the final sensing decision. This overcomes the hidden terminal problem and also improve the overall reliability of the decisions made about the presence or absence of a licensed user. Each unlicensed user sends the sensing results to the base station for the final decision. However, there exist some nodes which do not provide the correct sensing results to maximize their own profit which can highly degrade the CR network functionality. In this paper, a trust-aware model is proposed for the detection of misbehaving nodes such that their sensing reports can be filtered out from the final result. The performance evaluation of the proposed scheme is done by checking its robustness and efficiency against various possible attacks.