PAT: Privacy-Preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decoding

ArXi:2412.11390v3 Announce Type: replace-cross An electroencephalogram (EEG)-based brain-computer interface (BCI) enables direct communication between the brain and external devices. However, such systems face at least three major challenges in real-world applications: limited decoding accuracy, poor robustness, and privacy risks. Although prior studies have addressed one or two of these issues, methods that simultaneously improve accuracy, robustness, and privacy remain largely unexplored. In this paper, we propose Privacy-preserving Adversarial Transfer (PAT), a unified