Mercury: an automated remote side-channel attack to Nvidia deep learning accelerator

• Main Authors: Yan, Xiaobei, Lou, Xiaoxuan, Xu, Guowen, Qiu, Han, Guo, Shangwei, Chang, Chip Hong, Zhang, Tianwei
• 其他作者: School of Computer Science and Engineering
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2023
• 主題: Computer and Information Science; Profiled Side-Channel Attacks; DNN Accelerator; Sequence-to-Sequence Learning; FPGA; Model Extraction
• 在線閱讀: https://hdl.handle.net/10356/171839; https://fpt2023.org/index.html

DNN accelerators have been widely deployed in many scenarios to speed up the inference process and reduce the energy consumption. One big concern about the usage of the accelerators is the confidentiality of the deployed models: model inference execution on the accelerators could leak side-channel i...