Abnormal network access detection of power Internet of Things terminal layer equipment based on equipment portrait

Abstract

In the environment of the power Internet of Things, equipment network security is mainly analyzed through the physical signal characteristics of the equipment or a single flow characteristic, so as to realize the equipment network abnormality detection. Therefore, a method for detecting network abnormalities of power Internet of Things terminal equipment based on device fingerprints is proposed. Aiming at the problem of incomplete detection methods, a multi-dimensional matching device fingerprint model is established. Firstly, the basic information of the device is collected, such as IP, MAC, etc.; then the network traffic information of the device is analyzed to extract the characteristics of network traffic; then, the frequency of keyword and keyword group of service protocol is counted. The device fingerprint model is established by using the traffic and service characteristics. When the network anomaly occurs, the device fingerprint model can be found effectively. The experimental results show that the device fingerprint model can detect the abnormal behavior of the device.

Construction of intelligent terminal equipment for Electric Internet of Things based on edge computing model

“…At present, there are many problems in the perception layer of electric Internet of Things, such as complex access and connection management of massive devices, huge amount of data transmitted by terminals, non-sharing of perception information, low efficiency of real-time transmission and data processing. Therefore, it is urgent to learn from Internet thinking, apply efficient edge computing, container and other technical means, and build an integrated device of edge Internet of Things agent [3]. Based on the functional requirements of the overall architecture of the electric Internet of Things, the edge Internet of Things agent integration device realizes the goals of cross-professional data integration and sharing, regional energy autonomy and cloud-edge collaborative business processing on the edge side through the design of modules such as model management, framework management, application management, rule engine and message bus [4].…”