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Neighbors From Hell: Voltage Attacks Against Deep Learning Accelerators on Multi-Tenant FPGAs. (arXiv:2012.07242v2 [cs.CR] UPDATED)
July 11, 2022, 1:20 a.m. | Andrew Boutros, Mathew Hall, Nicolas Papernot, Vaughn Betz
cs.CR updates on arXiv.org arxiv.org
Field-programmable gate arrays (FPGAs) are becoming widely used accelerators
for a myriad of datacenter applications due to their flexibility and energy
efficiency. Among these applications, FPGAs have shown promising results in
accelerating low-latency real-time deep learning (DL) inference, which is
becoming an indispensable component of many end-user applications. With the
emerging research direction towards virtualized cloud FPGAs that can be shared
by multiple users, the security aspect of FPGA-based DL accelerators requires
careful consideration. In this work, we evaluate the …
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