3 papers
cs.CR2026
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…
cs.LG2026
Watch Out for the Lifespan: Evaluating Backdoor Attacks Against Federated Model Adaptation
Bastien Vuillod, Pierre-Alain Moellic, Jean-Max Dutertre
Large models adaptation through Federated Learning (FL) addresses a wide range of use cases and is enabled by Parameter-Efficient Fine-Tuning techniques such as Low-Rank Adaptation…
cs.CR2024
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…