With the continuous development of information technology, privacy protection in the Internet of Things (IoT) has attracted people 's attention. This paper summarizes and discusses the privacy and security issues faced by various levels of the IoT, and proposes an overall framework for privacy and security protection; investigates the research progress of ABE search security in the IoT, summarizes the types of firmware implementation defects in the IoT, analyzes the typical defect generation mechanisms, and summarizes the existing firmware defect detection methods from the perspectives of static analysis , symbol execution, fuzzy testing, program validation, and machine learning ; analyzes the existing mainstream access control models in the IoT, and summarizes the issues that need to be addressed in the future for blockchain based access control in the IoT. It further studies the recent achievements and progress of machine learning in the security protection of the IoT, and summarizes the privacy laws, especially the information protection law of the European Union (EU) in enterprises. Finally, we propose the main challenges that current research still faces and point out the direction of future research development.

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 paper 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 paper 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 paper 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 paper 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.

Cloud computing services have great convenience, but privacy security is a big obstacle of popularity. In the process result of privacy protection of cloud computing, it is difficult to choose the optimal strategy. In order to solve this problem, we propose a quantitative weight model of privacy information, use evolutionary game theory to establish a game model of attack protection, design the optimal protection strategy selection algorithm, and make the evolutionary stable equilibrium solution method from the limited rational constraint. In order to study the strategic dependence of the same game group, the classical dynamic replication equation is improved by using the incentive coefficient, an improved evolutionary game model of attack protection is constructed, the stability of equilibrium point is further analyzed by Jacobian matrix method, and the optimal selection strategy is obtained under different conditions. Finally, the correctness and validity of the model are verified by experiments, different strategies of the same group have the dual effects of promotion and inhibition, and the advantages of this paper are shown by comparing with other articles.

Budget factor is an important factor to measure the intensity of differential privacy, and its allocation scheme has a great impact on privacy protection. This paper studies the selection of the parameter ε in several cases of differential privacy. Firstly, this paper proposes a differential privacy protection parameter configuration method based on fault tolerance interval and analyzes the adversaryʼs fault tolerance under different noise distribution location parameters and scale parameters. Secondly, this paper proposes an algorithm to optimize the application scenarios of multiquery, studies the location parameters and scale parameters in detail, and proposes a differential privacy mechanism to solve the multiuser query scenarios. Thirdly, this paper proposes the differential privacy parameter selection methods based on the single attack and repeated attacks and calculates the upper bound of the parameter ε based on the sensitivity Δ q , the length of the fault tolerance interval L , and the success probability p as long as the fault tolerance interval. Finally, we have carried out a variety of simulation experiments to verify our research scheme and give the corresponding analysis results.