A Trusted Attestation Scheme for Data Source of Internet of Things in Smart City Based on Dynamic Trust Classification

The Internet of Things (IoT) in smart cities collects and transmits a large amount of time–space-sensitive information to realize feedback control. It bridges the gap between the information world and the real world. With the data-based feature, the security and credibility of the IoT mainly depend on whether the source of the data is trusted. Therefore, as the data collection and transmission entity, sensing nodes should be classified and proved the trustworthiness. However, the existing works failed to classify and measure the credibility of sensing nodes multidimensional in real time. The previous trust-proof methods also cannot effectively protect the key information. To address these problems, this article first proposes a multidimensional and fine-grained dynamic measurement method in a trusted computing environment. Then, a trust classification model of sensing nodes is presented, and a grouping mechanism of different trust levels is designed to identify malicious nodes. Finally, a threshold ring signature-based trust certification scheme is proposed for data source authentication. It can adequately protect the privacy information of the attestation node and has complete anonymity and traceability. Besides, the scheme has a shorter signature and high computational efficiency, which makes it also suitable for sensing nodes with limited computing resources. The simulation results show that the scheme has better dynamic adaptability and can effectively ensure the credibility of data sources under the premise of various attacks with accessible impact on the system.