{"title":"集中式认知无线网络中的信任管理模型","authors":"Qingqi Pei, Rui Liang, Hongning Li","doi":"10.1109/CyberC.2011.104","DOIUrl":null,"url":null,"abstract":"Cognitive radio network is composed of many cognitive users with sensing and learning modules, and its spectrum allocation changes from the primary user exclusive the resource to both users sharing the licensed spectrum. Trustworthy data of the perception and learning is the most important precondition whether the decision-making is fair and accurate. In this paper, a trust management model for centralized cognitive radio networks is proposed, which is on the base of the social sciences to build a trust mechanism through the whole cognitive cycle to solve the security threats brought by the untrustworthy entities, such as selfish, malicious, and faultless nodes. Analysis shows that the model can detect the malicious behavior and improve the fairness and robustness of the network.","PeriodicalId":227472,"journal":{"name":"2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"A Trust Management Model in Centralized Cognitive Radio Networks\",\"authors\":\"Qingqi Pei, Rui Liang, Hongning Li\",\"doi\":\"10.1109/CyberC.2011.104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cognitive radio network is composed of many cognitive users with sensing and learning modules, and its spectrum allocation changes from the primary user exclusive the resource to both users sharing the licensed spectrum. Trustworthy data of the perception and learning is the most important precondition whether the decision-making is fair and accurate. In this paper, a trust management model for centralized cognitive radio networks is proposed, which is on the base of the social sciences to build a trust mechanism through the whole cognitive cycle to solve the security threats brought by the untrustworthy entities, such as selfish, malicious, and faultless nodes. Analysis shows that the model can detect the malicious behavior and improve the fairness and robustness of the network.\",\"PeriodicalId\":227472,\"journal\":{\"name\":\"2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CyberC.2011.104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CyberC.2011.104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Trust Management Model in Centralized Cognitive Radio Networks
Cognitive radio network is composed of many cognitive users with sensing and learning modules, and its spectrum allocation changes from the primary user exclusive the resource to both users sharing the licensed spectrum. Trustworthy data of the perception and learning is the most important precondition whether the decision-making is fair and accurate. In this paper, a trust management model for centralized cognitive radio networks is proposed, which is on the base of the social sciences to build a trust mechanism through the whole cognitive cycle to solve the security threats brought by the untrustworthy entities, such as selfish, malicious, and faultless nodes. Analysis shows that the model can detect the malicious behavior and improve the fairness and robustness of the network.