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cs.CR2024
Is Difficulty Calibration All We Need? Towards More Practical Membership Inference Attacks
Yu He, Boheng Li, Yao Wang +4
The vulnerability of machine learning models to Membership Inference Attacks (MIAs) has garnered considerable attention in recent years. These attacks determine whether a data samp…
cs.CR2024★ 1 cited
A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack against Split Learning
Xiaoyang Xu, Mengda Yang, Wenzhe Yi +5
Split Learning (SL) is a distributed learning framework renowned for its privacy-preserving features and minimal computational requirements. Previous research consistently highligh…