Preprint
Sep 2026
Towards TEE-Certified DP: Verifiable Differentially Private Training on Legacy GPUs
Wide adoption of machine learning has created growing policy and regulatory demand for protecting sensitive training data, with differential privacy (DP) emerging as a key mechanism. Yet a less-studied problem is how to certify the faithful execution of DP during training: an external verifier should be able to check t...
Li Ge, Wenjie Qu, Weitao Feng et al.
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