Smart power network neighborhood network malicious user detection method based on power stealing suspicion degree

Abstract

The invention relates to a smart power network neighborhood network malicious user detection method based on power stealing suspicion degree. The method comprises three phases: user suspicion degree evaluation, binary detection tree establishment and malicious user detection. In the user suspicion degree evaluation phase, user power stealing records are analyzed, and predicted values of power consumption of users are compared with reported values of the users, thereby analyzing power stealing possibility of the users. On the basis of the power stealing suspicion degree of the users, a binary detection tree taking the users as leaf nodes is established, and the binary detection tree is taken as a logic structure for assisting the search of the malicious users. In the malicious user detection phase, top-down and deep first search rules are employed. A sub-detector only carries out practical detection on left children of the binary detection tree. According to the detector provided by theinvention, the vast majority of logic nodes on the binary detection tree can be skipped, so the malicious users in a smart power network neighborhood area can be positioned rapidly and accurately.

Description

technical field [0001] The invention relates to smart grid technology, in particular to a method for detecting malicious users in smart grid neighborhood networks based on the suspected degree of power theft. Background technique [0002] Smart grid, also known as "grid 2.0", integrates the latest information, communication and control technologies on the basis of traditional grids to realize bidirectional power flow and information flow. In the smart grid, the power grid company can control the operation status of the power grid in real time, timely discover, quickly diagnose and eliminate potential failures; it can ensure the safety of people, equipment and power grids in different situations such as natural disasters, external damage and computer attacks. At the same time, the smart grid can optimize the allocation of resources, improve the transmission capacity and utilization of equipment, and realize the optimal operation of the entire power system. By supporting the ...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problems of the existing smart grid malicious user detection methods, such as high deployment cost, high computational complexity, low detection accuracy, and possible violation of user privacy, the present invention proposes a smart grid neighborhood network based on the suspected degree of power theft. Malicious user detection method

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