{"title":"Countering byzantine attacks in cognitive radio networks","authors":"A. Rawat, Priyank Anand, Hao Chen, P. Varshney","doi":"10.1109/ICASSP.2010.5496102","DOIUrl":null,"url":null,"abstract":"Collaborative (or distributed) spectrum sensing has been shown to have various advantages in terms of spectrum utilization and robustness in cognitive radio networks (CRNs). The data fusion scheme is a key component of collaborative spectrum sensing. We have recently analyzed the problem of Byzantine attacks in CRNs, where malicious users send false sensing data to the fusion center (FC) leading to an increased probability of spectrum sensing error. In this paper, we propose a novel and easy to implement technique to counter Byzantine attacks in CRNs. In this approach, the FC identifies the attackers and removes them from the data fusion process. Our analysis indicates that the proposed scheme is robust against Byzantine attacks and can successfully remove the Byzantines in a short time span.","PeriodicalId":293333,"journal":{"name":"2010 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"76","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Acoustics, Speech and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2010.5496102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 76
Abstract
Collaborative (or distributed) spectrum sensing has been shown to have various advantages in terms of spectrum utilization and robustness in cognitive radio networks (CRNs). The data fusion scheme is a key component of collaborative spectrum sensing. We have recently analyzed the problem of Byzantine attacks in CRNs, where malicious users send false sensing data to the fusion center (FC) leading to an increased probability of spectrum sensing error. In this paper, we propose a novel and easy to implement technique to counter Byzantine attacks in CRNs. In this approach, the FC identifies the attackers and removes them from the data fusion process. Our analysis indicates that the proposed scheme is robust against Byzantine attacks and can successfully remove the Byzantines in a short time span.