4 papers
Model Poisoning Against Federated Model Adaptation with Chain of Bit-Flips
Bastien Vuillod, Kevin Hector, Pierre-Alain Moellic +2
Federated Learning (FL) allows a set of clients to collectively train a global model without sharing local training data. Giving the responsibility of the training to decentralized…
Fault Injection and Safe-Error Attack for Extraction of Embedded Neural Network Models
Kevin Hector, Pierre-Alain Moellic, Mathieu Dumont +1
Model extraction emerges as a critical security threat with attack vectors exploiting both algorithmic and implementation-based approaches. The main goal of an attacker is to steal…
Evaluation of Parameter-based Attacks against Embedded Neural Networks with Laser Injection
Mathieu Dumont, Kevin Hector, Pierre-Alain Moellic +2
Upcoming certification actions related to the security of machine learning (ML) based systems raise major evaluation challenges that are amplified by the large-scale deployment of…
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…