@inproceedings{1135,
  author = {Zihao Zhan and Zhenkai Zhang and Sisheng Liang and Fan Yao and Xenofon Koutsoukos},
  title = {Graphics Peeping Unit: Exploiting EM Side-Channel Information of GPUs to Eavesdrop on Your Neighbors},
  abstract = {As the popularity of graphics processing units (GPUs) grows rapidly in recent years, it becomes very critical to study and understand the security implications imposed by them. In this paper, we show that modern GPUs can “broadcast” sensitive information over the air to make a number of attacks practical. Specifically, we present a new electromagnetic (EM) side-channel vulnerability that we have discovered in many GPUs of both NVIDIA and AMD. We show that this vulnerability can be exploited to mount realistic attacks through two case studies, which are website fingerprinting and keystroke timing inference attacks. Our investigation recognizes the commonly used dynamic voltage and frequency scaling (DVFS) feature in GPU as the root cause of this vulnerability. Nevertheless, we also show that simply disabling DVFS may not be an effective countermeasure since it will introduce another highly exploitable EM side-channel vulnerability. To the best of our knowledge, this is the first work that studies realistic physical side-channel attacks on non-shared GPUs at a distance.},
  year = {2022},
  journal = {IEEE Symposium on Security and Privacy (SP)},
  pages = {1440-1457},
  month = {05/2022},
  publisher = {IEEE},
  address = {San Francisco, CA},
  issn = {2375-1207},
  isbn = {978-1-6654-1316-9},
  url = {https://ieeexplore.ieee.org/document/9833773},
  doi = {10.1109/SP46214.2022.9833773},
}