11378

Confidentiality Issues on a GPU in a Virtualized Environment

Clementine Maurice, Christoph Neumann, Olivier Heen, Aurelien Francillon
Technicolor, Rennes, France
Eighteenth International Conference on Financial Cryptography and Data Security (FC’14), 2014

@inproceedings{fc14GPU_maurice,

   title={Confidentiality Issues on a GPU in a Virtualized Environment},

   author={Clementine Maurice and Christoph Neumann and Olivier Heen and Aurelien Francillon},

   booktitle={Proceedings of the Eighteenth International Conference on Financial Cryptography and Data Security (FC’14)},

   series={FC 14},

   year={2014},

   month={March},

   location={Barbados},

   keywords={GPU security, virtualization, cloud computing},

   arate={31/138},

   affiliations={Eurecom, Technicolor}

}

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General-Purpose computing on Graphics Processing Units (GPGPU) combined to cloud computing is already a commercial success. However, there is little literature that investigates its security implications. Our objective is to highlight possible information leakage due to GPUs in virtualized and cloud computing environments. We provide insight into the different GPU virtualization techniques, along with their security implications. We systematically experiment and analyze the behavior of GPU global memory in the case of direct device assignment. We find that the GPU global memory is zeroed only in some configurations. In those configurations, it happens as a side effect of Error Correction Codes (ECC) and not for security reasons. As a consequence, an adversary can recover data of a previously executed GPGPU application in a variety of situations. These situations include setups where the adversary launches a virtual machine after the victim’s virtual machine using the same GPU, thus bypassing the isolation mechanisms of virtualization. Memory cleaning is not implemented by the GPU card itself and we cannot generally exclude the existence of data leakage in cloud computing environments. We finally discuss possible countermeasures for current GPU clouds users and providers.
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