A Lightweight Verifiable Trust based Data Collection (LVT-DC) approach is proposed to obtain credible data for mobile vehicles network, in which, a large number of IoT devices are deployed in smart city, and Mobile Vehicles (MVs) collect data from IoT devices and report data to cloud to construct various applications. First, some IoT devices are selected as core-IoT device whose data more than others. Then, Unmanned Aerial Vehicles (UAV) delivers a short verification code to each core-IoT devices and collects its data, and it embeds verification code into the data when the MVs collect it in order for cloud to check. Last, a verifiable trust inference method is proposed which includes two types of trust calculations. (a) Direct trust: MVs If the reported data cannot recover the verification code or is inconsistent with the UAV collection result, reduce the trust of the MVs, (b) Trust inference: If the data of a non-core-IoT devices reported by a MVs is inconsistent with the trusted MVs, then reduce its trust. After a large number of experimental results, the LVT-DC approach can quickly and accurately identify the credibility of the data collector and ensure credible data collection.

提出了一种基于轻量级可验证信任的数据收集（LVT-DC）方法来获取移动车辆网络的可信数据，其中智能城市中部署了大量物联网设备，移动车辆（MV）从物联网设备收集数据并将数据上报云端，构建各种应用。首先，一些物联网设备被选为核心物联网设备，其数据比其他设备多。然后，无人机 (UAV) 向每个核心物联网设备发送一个简短的验证码并收集其数据，并在 MV 收集数据时将验证码嵌入数据中，以便云端检查。最后，提出了一种可验证的信任推理方法，该方法包括两种类型的信任计算。(a) 直接信任：MVs 如果上报数据无法恢复验证码或与无人机采集结果不一致，降低 MV 的信任度， (b) 信任推断：如果 MV 报告的非核心物联网设备的数据与受信任的 MV 不一致，则降低其信任度。经过大量实验结果，LVT-DC方法可以快速准确地识别数据采集者的可信度，保证采集数据的可信度。