Differential Privacy for Deep and Federated Learning: A Survey
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DOI: 10.1109/access.2022.3151670
Abstract: 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 trained learning model. Differential privacy (DP)… read more here.
Keywords: deep federated; federated learning; survey; privacy ... See more keywords