4 papers
Improving Certified Robustness via Adversarial Distillation
Matteo Melis, Jesus Martinez Del Rincon, Vishal Sharma
Certified training aims to produce models whose predictions can be formally verified against adversarial perturbations, typically by optimising upper bounds on the worst-case loss…
FARM: Few-shot Adaptive Malware Family Classification under Concept Drift
Numan Halit Guldemir, Oluwafemi Olukoya, Jesús MartÃnez-del-Rincón
Malware classification models often suffer performance degradation under concept drift due to evolving threat landscapes and the emergence of novel malware families. This paper pre…
Privacy in Federated Learning with Spiking Neural Networks
Dogukan Aksu, Jesus Martinez del Rincon, Ihsen Alouani
Spiking neural networks (SNNs) have emerged as prominent candidates for embedded and edge AI. Their inherent low power consumption makes them far more efficient than conventional A…
Stealth by Conformity: Evading Robust Aggregation through Adaptive Poisoning
Ryan McGaughey, Jesus Martinez del Rincon, Ihsen Alouani
Federated Learning (FL) is a distributed learning paradigm designed to address privacy concerns. However, FL is vulnerable to poisoning attacks, where Byzantine clients compromise…