چکیده مقاله
The cognitive radio network CRNs has been developed in recent years for the optimal use of Available vacuum in the frequency spectrum In this network, Cooperate Spectrum Sensing CSS is used to combine the observations of all users In CRNs, security is one of the most important problems spectrum sensing data falsification SSDF attack is one of major challenges for CSS in CRNs, in which Malicious user are among honest users trying to change the information sent to the fusion center and thus make the fusion center s wrong decision In this paper, a method for defense against SSDF attack is proposed using MLP based neural network In this scheme, the weights of secondary users were constantly updated and finally the sensing results were combined in the fusion center based on their trusted weights Simulation results show that the proposed scheme can significantly reduce the effects of Spectrum Sensing Data Falsification SSDF attack even percentage of malicious users are more than trusted users
کلیدواژهها
نویسندگان
Zeynab Sadat Seyed Marvasti
Department of Computer Engineering, Islamic Azad University, Yazd ،Iran
Omid Abedi
Department of Computer Engineering, Shahid Bahonar University of Kerman, Iran
شیوه ارجاع
Seyed Marvasti, Zeynab Sadat and Abedi, Omid,1396,Detection of Malicious Node in Centralized Cognitive Radio Networks Based on MLP Neural Network,Fifth International Conference on Electrical and Computer Engineering with Emphasis on Indigenous Knowledge,Tehran
ارائهشده در
مجموعه مقالات پنجمین کنفرانس بین المللی مهندسی برق و کامپیوتر با تاکید بر دانش بومی19 بهمن 1396 · تهران