With the sharp increase in the number of intelligent devices, the Internet of Things (IoT) has gained more and more attention and rapid development in recent years. It effectively integrates the physical world with the Internet over existing network infrastructure to facilitate sharing data among intelligent devices. However, its complex and large-scale network structure brings new security risks and challenges to IoT systems. To ensure the security of data, traditional access control technologies are not suitable to be directly used for implementing access control in IoT systems because of their complicated access management and the lack of credibility due to centralization. In this paper, we proposed a novel attribute-based access control scheme for IoT systems that greatly simplifies the access management. We use blockchain technology to record the distribution of attributes in order to avoid single point failure and data tampering. The access control process has also been optimized to meet the need of high efficiency and lightweight calculation for IoT devices. Security and performance analysis show that our scheme could effectively resist multiple attacks and be efficiently implemented in IoT systems.

Traditional medical privacy data is at serious risk of disclosure, and many related cases have occurred over the years. For example, personal medical privacy data can be easily leaked to insurance companies, which not only compromises the privacy of individuals, but also hinders the healthy development of the medical industry. With the continuous improvement of cloud computing and big data technologies, the Internet of Things technology has been rapidly developed. RFID is one of the core technologies of the Internet of things. The application of RFID system to the medical system can effectively solve this problem of medical privacy. RFID tags in the system can collect useful information and conduct data exchange and processing with back-end server through the reader. The whole process of information interaction is mainly in the form of cipher text. In the context of the Internet of Things, the article presents a lightweight RFID medical privacy protection scheme. The scheme ensures security privacy of the collected data via secure authentication. The security analysis and evaluation about the scheme indicate that the protocol can effectively prevent the risk of medical privacy data being easily leaked.

Many artificial intelligence technologies have been applied for extracting useful information from massive industrial big data. However, the privacy issues are usually overlooked in many existing methods. In this article, we propose an anonymous and privacy-preserving federated learning scheme for the mining of industrial big data. We explored the effect of the proportion of shared parameters on the accuracy through experiments, and found that sharing partial parameters can almost achieve the accuracy of sharing all the parameters. On this basis, our proposed federated learning scheme reduces the privacy leakage by sharing fewer parameters between the server and each participant. Specifically, we leverage differential privacy on shared parameters with Gaussian mechanism to provide strict privacy preservation; the effect of different ε and δ on accuracy is tested; and we keep track of δ-when it reaches a certain threshold, training shall be stopped. What's more, we employ a proxy server as the middle layer between the server and all the participants to achieve anonymity of participants; it is worth noting that this can also reduce the communication burden on the federated learning server. Finally, we provide the security analysis and performance evaluations by comparing with other schemes.

Now, the authors’ life is full of vast amount of information, the era of information has arrived. So the content‐centric networks face severe challenges in dealing with a huge range of content requests, bringing protection and sharing concerns of the content. How to protect information in the network efficiently and securely for the upcoming 5G era has become a problem. The authors propose a scheme based on a blockchain to solve the privacy issues in content‐centric mobile networks for 5G. The authors implement the mutual trust between content providers and users. Besides, the openness and tamper‐resistant of the blockchain ledger ensure the access control and privacy of the provider. With the help of a miner, selected from users, the authors can maintain the public ledger expediently. Also, in return, the authors share the interesting data with low overhead, network delay and congestion, and then achieve green communication.