32 citations · 91 across the 60 of their papers we have counts for
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cs.LG2023★ 1 cited
Little is Enough: Boosting Privacy by Sharing Only Hard Labels in Federated Semi-Supervised Learning
Amr Abourayya, Jens Kleesiek, Kanishka Rao +4
In many critical applications, sensitive data is inherently distributed and cannot be centralized due to privacy concerns. A wide range of federated learning approaches have been p…
cs.LG2023★ 12 cited
AUTOLYCUS: Exploiting Explainable AI (XAI) for Model Extraction Attacks against Interpretable Models
Abdullah Caglar Oksuz, Anisa Halimi, Erman Ayday
Explainable Artificial Intelligence (XAI) aims to uncover the decision-making processes of AI models. However, the data used for such explanations can pose security and privacy ris…