2 citations · 5 across the 5 of their papers we have counts for
5 papers
Breaking Secure Aggregation: Label Leakage from Aggregated Gradients in Federated Learning
Zhibo Wang, Zhiwei Chang, Jiahui Hu +4
Federated Learning (FL) exhibits privacy vulnerabilities under gradient inversion attacks (GIAs), which can extract private information from individual gradients. To enhance privac…
Siamese Meets Diffusion Network: SMDNet for Enhanced Change Detection in High-Resolution RS Imagery
Jia Jia, Geunho Lee, Zhibo Wang +2
Recently, the application of deep learning to change detection (CD) has significantly progressed in remote sensing images. In recent years, CD tasks have mostly used architectures…
Towards Deep Learning Models Resistant to Transfer-based Adversarial Attacks via Data-centric Robust Learning
Yulong Yang, Chenhao Lin, Xiang Ji +5
Transfer-based adversarial attacks raise a severe threat to real-world deep learning systems since they do not require access to target models. Adversarial training (AT), which is…
Locate and Verify: A Two-Stream Network for Improved Deepfake Detection
Chao Shuai, Jieming Zhong, Shuang Wu +6
Deepfake has taken the world by storm, triggering a trust crisis. Current deepfake detection methods are typically inadequate in generalizability, with a tendency to overfit to ima…
DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery Clues
Kun Pan, Yin Yifang, Yao Wei +6
The malicious use and widespread dissemination of deepfake pose a significant crisis of trust. Current deepfake detection models can generally recognize forgery images by training…