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cs.CR2025
Arbitrary-Threshold Fully Homomorphic Encryption with Lower Complexity
Yijia Chang, Songze Li
Threshold fully homomorphic encryption (ThFHE) enables multiple parties to compute functions over their sensitive data without leaking data privacy. Most of existing ThFHE schemes…
cs.CR2024
Towards Understanding and Enhancing Security of Proof-of-Training for DNN Model Ownership Verification
Yijia Chang, Hanrui Jiang, Chao Lin +2
The great economic values of deep neural networks (DNNs) urge AI enterprises to protect their intellectual property (IP) for these models. Recently, proof-of-training (PoT) has bee…