2 papers
cs.CR2024
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…