31 citations · 45 across the 10 of their papers we have counts for
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cs.LG2021
BAARD: Blocking Adversarial Examples by Testing for Applicability, Reliability and Decidability
Xinglong Chang, Katharina Dost, Kaiqi Zhao +4
Adversarial defenses protect machine learning models from adversarial attacks, but are often tailored to one type of model or attack. The lack of information on unknown potential a…
cs.LG2021★ 31 cited
Membership Inference Attacks on Machine Learning: A Survey
Hongsheng Hu, Zoran Salcic, Lichao Sun +3
Machine learning (ML) models have been widely applied to various applications, including image classification, text generation, audio recognition, and graph data analysis. However,…