Abstract
Power system involves a large number of nodes and lines, and the topology is very complex. In such a complex network, node tamper detection needs to consider a variety of combinations and connection modes, which increases the complexity of the problem. Therefore, a new method of topological node tamper detection based on fuzzy graph theory is proposed. The feature difference values of topological nodes are extracted according to the node tampering feature vector. Detection of topological node similarity based on fuzzy graph-neural network. Based on this, the cost function of topological node tampering is established to obtain the Bayesian estimate of the tampering coefficient of the topological node transmission channel, and the detection of topological node tampering is completed. The experimental results show that the application time of the research method is shorter, the detection of power node tampering behavior is more comprehensive, and the tampering success rate is higher.
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