A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Privado: Practical and Secure DNN Inference with Enclaves
[article]
2019
arXiv
pre-print
Cloud providers are extending support for trusted hardware primitives such as Intel SGX. Simultaneously, the field of deep learning is seeing enormous innovation as well as an increase in adoption. In this paper, we ask a timely question: "Can third-party cloud services use Intel SGX enclaves to provide practical, yet secure DNN Inference-as-a-service?" We first demonstrate that DNN models executing inside enclaves are vulnerable to access pattern based attacks. We show that by simply observing
arXiv:1810.00602v2
fatcat:aomf6hdikjf5dhgpsjesydnq4e