Abstract：Aiming at the problem of low recognition accuracy of electricity stealing behavior，an electricity

stealing behavior recognition model based on joint neural network was proposed. Firstly，the acquired user

electricity consumption data was processed，and the user electricity consumption data was two-dimensionally

processed by using the Gramian angular field method. Then，for the electricity consumption data of different

dimensions，a user electricity stealing behavior recognition model based on the joint neural network was proposed，and the features of the one-dimensional electricity consumption data and the two-dimensional electricity

consumption data were extracted by using the convolutional neural network（CNN）and the bidirectional long shortterm memory（BiLSTM）neural network. The case analysis shows that the proposed joint neural network model has an accuracy rate of more than 90% for the recognition of electricity stealing behavior，which proves that the established evaluation model provides a practical solution to the electricity stealing problem.

      Key words：electricity stealing behavior；joint neural network；data mining