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Aiming at the problems of classical gauss template attacks, based on the analysis of the advantages of convolutional neural network, a new method based on convolution neural network for encrypting chip side-channel template attack is proposed. This method can deal with high-dimensional data effectively, and it can achieve infinite approxima -tion of data by adjusting weights and biases constantly, and clarify the precise relationship between classifications, and improve the accuracy of template characterization.Selects the AT89C52 microcontroller (MCU) running AES encryption algorithm first round XOR operation is the point of attack, compared with traditional template attacks. Experimental results show that although the success rate of matching is slightly lower than that of traditional template attacks, the model structure and hyperparameter still need to be further optimized. However, the new method has greater advantages in dealing with high-dimensional feature points than traditional template attacks.