98 citations · 172 across the 21 of their papers we have counts for
5 papers · 1 filter
On the Adversarial Robustness of Graph Neural Networks with Graph Reduction
Kerui Wu, Ka-Ho Chow, Wenqi Wei +1
As Graph Neural Networks (GNNs) become increasingly popular for learning from large-scale graph data across various domains, their susceptibility to adversarial attacks when using…
Personalized Privacy Protection Mask Against Unauthorized Facial Recognition
Ka-Ho Chow, Sihao Hu, Tiansheng Huang +1
Face recognition (FR) can be abused for privacy intrusion. Governments, private companies, or even individual attackers can collect facial images by web scraping to build an FR sys…
Visualizing the Shadows: Unveiling Data Poisoning Behaviors in Federated Learning
Xueqing Zhang, Junkai Zhang, Ka-Ho Chow +6
This demo paper examines the susceptibility of Federated Learning (FL) systems to targeted data poisoning attacks, presenting a novel system for visualizing and mitigating such thr…
Robust Few-Shot Ensemble Learning with Focal Diversity-Based Pruning
Selim Furkan Tekin, Fatih Ilhan, Tiansheng Huang +4
This paper presents FusionShot, a focal diversity optimized few-shot ensemble learning approach for boosting the robustness and generalization performance of pre-trained few-shot m…
Imperio: Language-Guided Backdoor Attacks for Arbitrary Model Control
Ka-Ho Chow, Wenqi Wei, Lei Yu
Natural language processing (NLP) has received unprecedented attention. While advancements in NLP models have led to extensive research into their backdoor vulnerabilities, the pot…