期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2019
卷号：15
期号：9
页码：1
DOI：10.1177/1550147719870645
出版社：Hindawi Publishing Corporation
摘要：To detect the primary user’s activity accurately in cognitive radio sensor networks, cooperative spectrum sensing is recommended to improve the sensing performance and the reliability of spectrum-sensing process. However, spectrum-sensing data falsification attack being launched by malicious users may lead to fatal mistake of global decision about spectrum availability at the fusion center. It is a tough task to mitigate the negative effect of spectrum-sensing data falsification attack and even eliminate these attackers from the network. In this article, we first discuss the randomly false attack model and analyze the effects of two classes of attacks, individual and collaborative, on the global sensing performance at the fusion center. Afterwards, a linear weighted combination scheme is designed to eliminate the effects of the attacks on the final sensing decision. By evaluating the received sensing result, each user can be assigned a weight related to impact factors, which includes result consistency degree and data deviation degree. Furthermore, an adaptive reputation evaluation mechanism is introduced to discriminate malicious and honest sensor node. The evaluation is conducted through simulations, and the results reveal the benefits of the proposed in aspect of mitigation of spectrum-sensing data falsification attack.
关键词：Spectrum sensing; reputation degree; data falsification attack; cognitive radio sensor networks
其他关键词：Spectrum sensing ; reputation degree ; data falsification attack ; cognitive radio sensor networks
