Hello all,
I hope you are doing well.
I would like to know about effective and suggested approaches to protecting sensitive data used in Deep Learning models.
Thanks for sharing your thoughts.
You can look into Privacy Preserving Machine Learning, Federated Learning, Differential Privacy, Homomorphic encryption etc.
Also Look into 'Openmined'. They are experts on this.
It depends on the nature of your data. For instance, in textual data, some encryption techniques can help out while in image data, applying filters and its removal at the end, can help out.
It depends on the meaning of " protecting", the nature of your data and the use case ( off-line learning, online, edge, distributed..)
https://cloud.google.com/architecture/sensitive-data-and-ml-datasets
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