5 citations · 11 across the 11 of their papers we have counts for
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cs.CR2024★ 1 cited
Exploring the Adversarial Frontier: Quantifying Robustness via Adversarial Hypervolume
Ping Guo, Cheng Gong, Xi Lin +2
The escalating threat of adversarial attacks on deep learning models, particularly in security-critical fields, has underscored the need for robust deep learning systems. Conventio…
cs.CR2024★ 5 cited
L-AutoDA: Leveraging Large Language Models for Automated Decision-based Adversarial Attacks
Ping Guo, Fei Liu, Xi Lin +2
In the rapidly evolving field of machine learning, adversarial attacks present a significant challenge to model robustness and security. Decision-based attacks, which only require…
cs.CR2024
PuriDefense: Randomized Local Implicit Adversarial Purification for Defending Black-box Query-based Attacks
Ping Guo, Xiang Li, Zhiyuan Yang +3
Black-box query-based attacks constitute significant threats to Machine Learning as a Service (MLaaS) systems since they can generate adversarial examples without accessing the tar…