Compared with centralized cloud computing frameworks, edge computing deploys additional “edge servers” between a cloud center and on-site intelligent devices to support those devices to quickly and efficiently complete computing tasks and event processing. In an edge computing system, there are a large number of on-site intelligent devices and heterogeneous edge computing servers. Also, stored data is sensitive and requires high privacy. These characteristics of edge computing systems make it difficult to ensure network security. Solving information and network security of edge computing systems is the key to the large-scale industrialization of edge computing technology. However, due to the limitations of computing capacity, network capacity, and storage capacity of edge server devices and on-site intelligent devices, traditional computer network security technology may not fully meet the requirements. Analyzing effective sensitive data protection technologies suitable for edge computing systems, such as federated learning, lightweight encryption, confused and virtual location information, and anonymous identity authentication, and exploring new technologies such as artificial intelligence and blockchain to prevent malicious attacks in edge computing will greatly promote the industrial development of edge computing.