Power side-channel analysis recovers DNN architecture and parameters at 96.5% average accuracy on real embedded devices.
Imagenet large scale visual recognition challenge,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2019 2verdicts
UNVERDICTED 2representative citing papers
FOSNet fuses object and scene features via CNN and uses scene coherence loss to report SOTA accuracies of 60.14% on Places2 and 90.37% on MIT Indoor67.
citing papers explorer
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Open DNN Box by Power Side-Channel Attack
Power side-channel analysis recovers DNN architecture and parameters at 96.5% average accuracy on real embedded devices.
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FOSNet: An End-to-End Trainable Deep Neural Network for Scene Recognition
FOSNet fuses object and scene features via CNN and uses scene coherence loss to report SOTA accuracies of 60.14% on Places2 and 90.37% on MIT Indoor67.