[1] [1] HUA Weizhe, ZHANG Zhiru, SUH G E. Reverse engineering convolutional neural networks through side-channel information leaks [C]// 2018 the 55th ACM/ESDA/IEEE Design Automation Conference (DAC). San Francisco,CA,USA:IEEE, 2018:1-6.

[2] [2] HONG S, DAVINROY M, KAYA Y, et al. Security analysis of deep neural networks operating in the presence of cache side-channel attacks[EB/OL]. (2018-10-08)[2021-05-21]. https://doi.org/10.48550/arXiv.1810.03487.

[3] [3] BATINA L,BHASIN S,JAP D,et al. CSI NN:reverse engineering of neural network architectures through electromagnetic side channel[C]// Proceedings of the 28th USENIX Conference on Security Symposium. Santa Clara,CA,USA:USENIX Association, 2019:515-532.

[4] [4] YU Honggang, MA Haocheng, YANG Kaichen, et al. DeepEM: deep neural networks model recovery through EM side-channel information leakage[C]// 2020 IEEE International Symposium on Hardware Oriented Security and Trust(HOST). San Jose,CA, USA:IEEE, 2020:209-218.

[5] [5] ABADI M,BARHAM P,CHEN Jianmin,et al. TensorFlow:a system for large-scale machine learning[C]// Proceedings of the 12th USENIX Conference on Operating Systems Design and Implementation. Savannah, GA, USA: USENIX Association, 2016: 265-283.

[6] [6] PASZKE A,GROSS S,CHINTALA S,et al. Automatic differentiation in PyTorch[C]// The 31st Conference on Neural Information Processing Systems(NIPS 2017). Long Beach,CA,USA:[s.n.], 2017:1-4.

[7] [7] HE Kaiming,ZHANG Xiangyu,REN Shaoqing,et al. Deep residual learning for image recognition[C]// 2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Las Vegas,NV,USA:IEEE, 2016:770-778.

[8] [8] DENG Jia, DONG Wei, SOCHER R, et al. ImageNet: a large-scale hierarchical image database[C]// 2009 IEEE Conference on Computer Vision and Pattern Recognition. Miami,FL,USA:IEEE, 2009:248-255.

[9] [9] LIN T Y,MAIRE M,BELONGIE S,et al. Microsoft COCO:common objects in context[C]// Computer Vision-ECCV 2014. Cham: Springer, 2014:740-755.

[10] [10] LECUN Y,BOTTOU L,BENGIO Y,et al. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 1998,86(11):2278-2324.

[11] [11] KRIZHEVSKY A, SUTSKEVER I, HINTON G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 2017,60(6):84-90.

[12] [12] SIMONYAN K, ZISSERMAN A. Very deep convolutional networks for large-scale image recognition[EB/OL]. (2014-09-04). https://doi.org/10.48550/arXiv.1409.1556.