Search Results for author:
Found 1 papers, 0 papers with code
Mercury: An Automated Remote Side-channel Attack to Nvidia Deep Learning Accelerator
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 information, which enables an adversary to preciously recover the model details.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
