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Báo cáo hóa học: "Research Article Securing Collaborative Spectrum Sensing against Untrustworthy Secondary Users in Cognitive Radio Networks"

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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Securing Collaborative Spectrum Sensing against Untrustworthy Secondary Users in Cognitive Radio Networks | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 695750 15 pages doi 10.1155 2010 695750 Research Article Securing Collaborative Spectrum Sensing against Untrustworthy Secondary Users in Cognitive Radio Networks Wenkai Wang 1 Husheng Li 2 Yan Lindsay Sun 1 and Zhu Han3 1 Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston RI02881 USA 2Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN 37996 USA 3Department of Electrical and Computer Engineering University of Houston Houston TX 77004 USA Correspondence should be addressed to Wenkai Wang wenkai@ele.uri.edu Received 14 May 2009 Revised 14 September 2009 Accepted 1 October 2009 Academic Editor Jinho Choi Copyright 2010 Wenkai Wang et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Cognitive radio is a revolutionary paradigm to migrate the spectrum scarcity problem in wireless networks. In cognitive radio networks collaborative spectrum sensing is considered as an effective method to improve the performance of primary user detection. For current collaborative spectrum sensing schemes secondary users are usually assumed to report their sensing information honestly. However compromised nodes can send false sensing information to mislead the system. In this paper we study the detection of untrustworthy secondary users in cognitive radio networks. We first analyze the case when there is only one compromised node in collaborative spectrum sensing schemes. Then we investigate the scenario that there are multiple compromised nodes. Defense schemes are proposed to detect malicious nodes according to their reporting histories. We calculate the suspicious level of all nodes based on their reports. The reports from nodes with

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