A federated, privacy-preserving RDSN framework for encrypted image reconstruction whose local differential privacy mechanism is not actually differentially private because it releases low-frequency DCT coefficients without noise.
Recent advances of differen- tial privacy in centralized deep learning: A systematic survey,
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PPFL-RDSN: Privacy-Preserving Federated Learning-based Residual Dense Spatial Networks for Encrypted Lossy Image Reconstruction
A federated, privacy-preserving RDSN framework for encrypted image reconstruction whose local differential privacy mechanism is not actually differentially private because it releases low-frequency DCT coefficients without noise.