Privacy-Preserving Data Synthetisation for Secure Information Sharing. (arXiv:2212.00484v1 [cs.LG])

We can protect user data privacy via many approaches, such as statistical
transformation or generative models. However, each of them has critical
drawbacks. On the one hand, creating a transformed data set using conventional
techniques is highly time-consuming. On the other hand, in addition to long
training phases, recent deep learning-based solutions require significant
computational resources. In this paper, we propose PrivateSMOTE, a technique
designed for competitive effectiveness in protecting cases at maximum risk of
re-identification while requiring much less …

data information information sharing privacy sharing