JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2019, Vol. 54 ›› Issue (1): 60-66.doi: 10.6040/j.issn.1671-9352.3.2018.004

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Comparative study on neural network structures in power analysis

LIU Biao, LU Zhe, HUANG Yu-wei, JIAO Meng, LI Quan-qi, XUE Rui   

  1. Management Department, Beijing Electronic Science and Technology Institution, Beijing 100071, China
  • Published:2019-01-23

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Abstract: In order to explore the difference of different neural networks used in power analysis, we use DPA_Contest_V4 dataset to complete our experiment. After the mask is cracked, the deep neural network and the traditional machine learning like SVM are firstly used. Then, the impact of the changes in the structure of the neural network model on the experimental results is analyzed. Finally, a comprehensive comparison of different network models is made by combining the cyclic neural network. The experimental results show that the neural network model is superior to the traditional machine learning model and the recurrent neural network model is superior to the deep neural network model when experimental conditions are the same. Among them, the activation functions of neural networks with different layers are different, which will lead to great changes in the experimental results.

Key words: deep learning, neural network, power analysis

CLC Number: 

  • TP309.2
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