Homomorphic Encryption: Ensuring Privacy and Compliance in Data Security 🔒

Compliance with recent privacy laws and confidentiality regulations requires that most, if not all, of the data and the computation must be kept in a secure environment, usually in-house, and not outsourced to cloud or multi-tenant shared environments. IBM Research is focused on how to apply advanced cryptographic schemes such as Homomorphic Encryption (HE) to protect the privacy and confidentiality of both the data during the training of ML models as well as the models themselves, and as a consequence, the prediction task can also be protected.