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cs.CR2026
Revisiting Privacy Leakage in Machine Unlearning: Membership Inference Beyond the Forgotten Set
Jie Fu, Nima Naderloui, Da Zhong +2
Machine unlearning (MU) has emerged as a key mechanism for ensuring data privacy and regulatory compliance by enabling models to forget specific training samples. However, recent s…
cs.LG2026
Adversarial Attacks on Locally Private Graph Neural Networks
Matta Varun, Ajay Kumar Dhakar, Yuan Hong +1
Graph neural network (GNN) is a powerful tool for analyzing graph-structured data. However, their vulnerability to adversarial attacks raises serious concerns, especially when deal…