Research on Data Privacy Protection Mechanisms in the Internet of Things

Abstract

With the in-depth popularization of Internet of Things (IoT) technology, the access of massive terminal devices has brought unprecedented risks of data privacy leakage. This paper focuses on the issue of data privacy protection in the IoT environment, and systematically analyzes the privacy threats faced in four stages: data collection, transmission, storage and application, including illegal sniffing, man-in-the-middle attacks, cloud platform leakage and data mining attacks. On this basis, this paper elaborates on four core privacy protection mechanisms: data anonymization technologies based on K-anonymity and differential privacy, encryption technologies centered on lightweight encryption and homomorphic encryption, blockchain-based distributed trust mechanisms, and architectural innovations combining edge computing and federated learning. Through an in-depth analysis of the principles, application scenarios, advantages and disadvantages of these technologies, this paper reveals the limitations of single technologies and emphasizes the necessity of constructing a multi-level and collaborative protection system. Finally, the paper prospects the development trends of IoT privacy protection in terms of compliance requirements and the integration of emerging technologies, providing a theoretical reference for building a secure and trusted IoT environment.