2 papers
cs.CR2026
Embedding Asymmetry as Attack Signal: Detecting and Defending Active Label Inference in Vertical Federated Learning
Soumya Swagata Biswas, Muhammad Abdullah Adnan
Vertical federated learning lets organizations train a shared model over features they hold separately, while one party keeps the labels private. The active label inference attack…
cs.CR2026
XFED: Non-Collusive Model Poisoning Attack Against Byzantine-Robust Federated Classifiers
Israt Jahan Mouri, Muhammad Ridowan, Muhammad Abdullah Adnan
Model poisoning attacks pose a significant security threat to Federated Learning (FL). Most existing model poisoning attacks rely on collusion, requiring adversarial clients to coo…