Khalid A. Alissa

Investigating privacy leakage in distributed deep learning for medical imaging through gradient inversion attacks

This work investigates privacy leakage in federated learning using the NIH Chest X-ray dataset by evaluating the susceptibility of three deep learning architectures namely Simple CNN, ResNet-50, and EfficientNet to gradient-based image reconstruction attacks and suggests that model architecture can deeply influence the...