Differential privacy for deep and federated learning: A survey

A El Ouadrhiri, A Abdelhadi - IEEE access, 2022‏ - ieeexplore.ieee.org
Users' privacy is vulnerable at all stages of the deep learning process. Sensitive information
of users may be disclosed during data collection, during training, or even after releasing the …

Local Differential Privacy Is Equivalent to Contraction of an -Divergence

S Asoodeh, M Aliakbarpour… - 2021 IEEE International …, 2021‏ - ieeexplore.ieee.org
We investigate the local differential privacy (LDP) guarantees of a randomized privacy
mechanism via its contraction properties. We first show that LDP constraints can be …