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

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

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...

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Bibliographic Details
Main Authors: Yan, Xiaobei, Lou, Xiaoxuan, Xu, Guowen, Qiu, Han, Guo, Shangwei, Chang, Chip Hong, Zhang, Tianwei
Other Authors: School of Computer Science and Engineering
Format: Conference Paper
Language:English
Published: 2023
Subjects:
Computer and Information Science
Profiled Side-Channel Attacks
DNN Accelerator
Sequence-to-Sequence Learning
FPGA
Model Extraction
Online Access:https://hdl.handle.net/10356/171839
https://fpt2023.org/index.html

Internet

https://hdl.handle.net/10356/171839
https://fpt2023.org/index.html

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