Welcome to the resource topic for 2020/1031
Title:
Profiled Deep Learning Side-Channel Attack on a Protected Arbiter PUF Combined with Bitstream Modification
Authors: Yang Yu, Michail Moraitis, Elena Dubrova
Abstract:In this paper we show that deep learning can be used to identify the shape of power traces corresponding to the responses of a protected arbiter PUF implemented in FPGAs. To achieve that, we combine power analysis with bitstream modification. We train a CNN classifier on two 28nm XC7 FPGAs implementing 128-stage arbiter PUFs and then classify the responses of PUFs from two other FPGAs. We demonstrate that it is possible to reduce the number of traces required for a successful attack to a single trace by modifying the bitstream to replicate PUF responses.
ePrint: https://eprint.iacr.org/2020/1031
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