The Internet of Things (IoT) is used in homes and hospitals and deployed outdoors to control and report environmental changes, prevent fires, and perform many more beneficial functions. However, all these benefits come at the tremendous risk of loss of privacy and security issues. To protect the IoT, much research has been carried out to address these risks and find better ways to eliminate them or at least minimize their impact on user privacy and security requirements. This article expounds various network security risks faced by the IoT, analyzes their impacts, discusses risk assessment methods, shows the causes and hazards of these threats, and proposes an overall framework of privacy security protection. This article summarizes the typical defect types in the implementation of IoT firmware, analyzes the generation mechanism of typical defects from the perspectives of fuzzy testing, program verification and machine learning, and compares and expounds the progress of security research for several common IoT protocols. This article analyzes and summarizes the mainstream access control model in the existing IoT and the access control model after using the blockchain and builds a new integrated AIoT architecture for intelligent information processing. Finally, this article expounds on the current legal development status of the privacy protection of network information in various countries and discusses the future prospects of the IoT.

Internet of Things (IoT) aims at connecting all objects through the Internet. The IoT-based smart city is the concept of employing IoT devices to manage cities more easily, quickly and effectively. Recently, a new paradigm has emerged in the networking world, called software-defined networking (SDN), which separates the control data plane and the data plane. On the other hand, IoT devices embedded in a smart city often detect sensitive data. It is of paramount importance to prevent leaking this data unintentionally, known as privacy preserving. Although there are some methods to preserve data privacy in smart cities, they are either expensive or cannot preserve privacy efficiently. Intending to provide an efficient privacy preserving in a cost-effective smart city, we propose a novel method called differential privacy (DP)-preserving Smart City (DPSmartCity). It maintains the privacy of IoT devices’ sensitive data by equipping the environment with SDN technologies and leveraging a customized DP technique while its distribution changes frequently. We then mathematically investigate the DP aspect of the given algorithms by providing several proofs. The evaluation results show the effectiveness of the proposed method for diffident parameters, such as overload amount and latency points. Based on our threat model, it is 25.89% more robust against unintentional disclosure of sensitive data from a penetration point of view.