Mini toolsDefinition
Techniques and methods that enable machine learning while protecting sensitive data and maintaining individual privacy.
Detailed Explanation
PPML combines machine learning with privacy-enhancing technologies like differential privacy homomorphic encryption and secure multi-party computation. It enables model training and inference while ensuring that sensitive information cannot be extracted from the model or its outputs even through sophisticated attacks.
Use Cases
Healthcare data analysis Financial service collaboration Privacy-conscious recommendation systems Secure federated learning implementations
