In the Internet of Things (IoT) system, data leakage can easily occur due to the differing security of edge devices and the different processing methods of data in the transmission process. Blockchain technology has the advantages of good non-tamperability, decentralization, de-trust, openness, and transparency, and it can protect data security on the Internet of Things. This research integrates the means by which data flow can be combined with blockchain technology to prevent privacy leakage throughout the entire transportation process from sender to receiver. Through a keyword search of the last five years, 94 related papers in Web of Science and IEEE Xplore were extracted and the complex papers and frameworks explained using a reconstruction graph. The data processing process is divided into five modules: data encryption, data access control, data expansion, data storage, and data visualization. A total of 11 methods combining blockchain technology to process IoT data were summarized. The blockchain application technology in the IoT field was summarized objectively and comprehensively, and a new perspective for studying IoT data flow was given.

Data publishing techniques have led to breakthroughs in several areas. These tools provide a promising direction. However, when they are applied to private or sensitive data such as patient medical records, the published data may divulge critical patient information. In order to address this issue, we propose a differential private data publishing method (SSKM_DP) based on the SFLA-Kohonen network, which perturbs sensitive attributes based on the maximum information coefficient to achieve a trade-off between security and usability. Additionally, we introduced a single-population frog jump algorithm (SFLA) to optimize the network. Extensive experiments on benchmark datasets have demonstrated that SSKM_DP outperforms state-of-the-art methods for differentially private data publishing techniques significantly.