4 accepted papers
Deep learning-based watermarking has made remarkable progress in recent years. To achieve robustness against various distortions, current methods commonly adopt a training strategy where a \underline s ingle \underline r andom \underline d istortion (SRD) is chosen as the noise layer in each trainin
Backdoor attacks pose a severe threat to federated graph learning (FGL), where malicious clients can inject hidden triggers into the global model without being detected. Defending against such attacks is particularly challenging due to the complex graph structures and the stealthy nature of trigger
Federated Learning (FL), a privacy-preserving decentralized machine learning framework, has been shown to be vulnerable to backdoor attacks. Current research primarily focuses on the Single-Label Backdoor Attack (SBA), wherein adversaries share a consistent target. However, a critical fact is overlo…
Self-supervised learning (SSL) is capable of learning remarkable representations from centrally available data. Recent works further implement federated learning with SSL to learn from rapidly growing decentralized unlabeled images (e.g., from cameras and phones), often resulting from privacy constr…