4 papers
A Closer Look at Evaluating the Bit-Flip Attack Against Deep Neural Networks
Kevin Hector, Mathieu Dumont, Pierre-Alain Moellic +1
Deep neural network models are massively deployed on a wide variety of hardware platforms. This results in the appearance of new attack vectors that significantly extend the standa…
An Overview of Laser Injection against Embedded Neural Network Models
Mathieu Dumont, Pierre-Alain Moellic, Raphael Viera +2
For many IoT domains, Machine Learning and more particularly Deep Learning brings very efficient solutions to handle complex data and perform challenging and mostly critical tasks.…
Luring of transferable adversarial perturbations in the black-box paradigm
Rémi Bernhard, Pierre-Alain Moellic, Jean-Max Dutertre
The growing interest for adversarial examples, i.e. maliciously modified examples which fool a classifier, has resulted in many defenses intended to detect them, render them inoffe…
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks
Rémi Bernhard, Pierre-Alain Moellic, Jean-Max Dutertre
As the will to deploy neural networks models on embedded systems grows, and considering the related memory footprint and energy consumption issues, finding lighter solutions to sto…