Internet of Things (IoT) is considered the future network to support wireless communications. To realize an IoT network, sufficient spectrum should be allocated for the rapidly increasing IoT devices. Through cognitive radio, unlicensed IoT devices exploit cooperative spectrum sensing (CSS) to opportunistically access a licensed spectrum without causing harmful interference to licensed primary users (PUs), thereby effectively improving the spectrum utilization. However, an open access cognitive IoT allows abnormal IoT devices to undermine the CSS process. Herein, we first establish a hard‐combining attack model according to the malicious behavior of falsifying sensing data. Subsequently, we propose a weighted sequential hypothesis test (WSHT) to increase the PU detection accuracy and decrease the sampling number, which comprises the data transmission status‐trust evaluation mechanism, sensing data availability, and sequential hypothesis test. Finally, simulation results show that when various attacks are encountered, the requirements of the WSHT are less than those of the conventional WSHT for a better detection performance.

中文翻译：

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顺序融合可防御认知物联网的感知数据篡改攻击

物联网（IoT）被认为是支持无线通信的未来网络。为了实现物联网网络，应为迅速增长的物联网设备分配足够的频谱。通过认知无线电，未经许可的IoT设备可利用协作频谱感知（CSS）机会性地访问许可的频谱，而不会对许可的主要用户（PU）造成有害干扰，从而有效地提高了频谱利用率。但是，开放式认知物联网允许异常物联网设备破坏CSS流程。在此，我们首先根据伪造传感数据的恶意行为建立了一种硬组合攻击模型。随后，我们提出了加权顺序假设检验（WSHT），以提高PU检测的准确性并减少采样数，其中包括数据传输状态信任评估机制，感知数据可用性和顺序假设检验。最后，仿真结果表明，在遇到各种攻击时，WSHT的要求比常规WSHT的要求要低，从而具有更好的检测性能。