PySyft is a Framework for Bringing Privacy to Deep Learning Models.

Trust is a key factor in the implementation of deep learning applications. From training to optimization, the lifecycle of a deep learning model is tied to trusted data exchanges between different parties. That dynamic is certainly effective for a lab environment but results vulnerable to several all sorts of security attacks that manipulate the trusted relationships between the different participants in a model. Let's take the example of a credit scoring model based that uses financial transaction to classify the credit risk for a specific customer. The traditional mechanisms for training or optimizing a model assume that the entities performing those actions will have full access to those financial datasets which opens the door to all sorts of privacy risks.