Due to the increase in industrial applications of Internet of Things (IoT), number of internet connected devices have been increased accordingly. This has resulted in big challenges in terms of accessibility, scalability, connectivity and adaptability. IoT is capable of creating connections between devices on wireless medium but the utilization of scarce spectrum in efficient manner for the establishment of these connections is the biggest concern. To accommodate spectrum allocation problem different radio technologies are being utilized. One of the most efficient technique being used is cognitive radio, which dynamically allocate the unlicensed spectrum for IoT applications. Spectrum sensing being the fundamental component of Cognitive Radio Network (CRN) is threatened by security attacks. Process of spectrum sensing is disturbed by the malicious user (MU) which attacks the primary signal detection and affects the accuracy of sensing outcome. The presence of such MU in system, sending false sensing data can degrade the performance of cognitive radios. Therefore, in this article a blockchain based method is proposed for the MU detection in network. By using this method an MU can easily be discriminated from a reliable user through cryptographic keys. The efficiency of the proposed mechanism is analyzed through proper simulations using MATLAB. Consequently, this mechanism can be deployed for the validation of participating users in the process of spectrum sensing in CRN for IoTs.

由于物联网（IoT）在工业领域的应用不断增加，因此与互联网连接的设备数量也相应增加。这在可访问性，可伸缩性，连接性和适应性方面带来了巨大挑战。物联网能够在无线介质上的设备之间创建连接，但是最大的关注是如何有效利用稀有频谱来建立这些连接。为了适应频谱分配问题，正在使用不同的无线电技术。正在使用的最有效的技术之一是认知无线电，它可以为物联网应用动态分配未经许可的频谱。频谱感知是认知无线电网络（CRN）的基本组成部分，受到安全攻击的威胁。频谱检测过程受到恶意用户（MU）的干扰，恶意用户攻击主要信号检测并影响检测结果的准确性。系统中此类MU的存在，发送错误的感知数据会降低认知无线电的性能。因此，本文提出了一种基于区块链的网络中MU检测方法。通过使用此方法，可以轻松地通过加密密钥将MU与可靠的用户区分开。通过使用MATLAB进行适当的仿真，分析了所提出机制的效率。因此，可以将这种机制部署到IoT的CRN中频谱感知过程中的参与用户验证。发送错误的感应数据会降低认知无线电的性能。因此，本文提出了一种基于区块链的网络中MU检测方法。通过使用此方法，可以轻松地通过加密密钥将MU与可靠的用户区分开。通过使用MATLAB进行适当的仿真，分析了所提出机制的效率。因此，可以将这种机制部署到IoT的CRN中频谱感知过程中的参与用户验证。发送错误的感应数据会降低认知无线电的性能。因此，本文提出了一种基于区块链的网络中MU检测方法。通过使用此方法，可以轻松地通过加密密钥将MU与可靠的用户区分开。通过使用MATLAB进行适当的仿真，分析了所提出机制的效率。因此，可以将这种机制部署到IoT的CRN中频谱感知过程中的参与用户验证。