98 citations · 474 across the 39 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…
Boosting Imperceptibility of Stable Diffusion-based Adversarial Examples Generation with Momentum
Nashrah Haque, Xiang Li, Zhehui Chen +4
We propose a novel framework, Stable Diffusion-based Momentum Integrated Adversarial Examples (SD-MIAE), for generating adversarial examples that can effectively mislead neural net…
Data Poisoning and Leakage Analysis in Federated Learning
Wenqi Wei, Tiansheng Huang, Zachary Yahn +3
Data poisoning and leakage risks impede the massive deployment of federated learning in the real world. This chapter reveals the truths and pitfalls of understanding two dominating…
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Wenqi Wei, Ling Liu
Emerging Distributed AI systems are revolutionizing big data computing and data processing capabilities with growing economic and societal impact. However, recent studies have iden…
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…