Efficient AES-GCM decryption under Homomorphic Encryption

Abstract

Computation delegation to untrusted third-party while maintaining data confidentiality is possible with homomorphic encryption (HE). However, in many cases, the data was encrypted using another cryptographic scheme such as AES-GCM. Hybrid encryption (a.k.a Transciphering) is a technique that allows moving between cryptosystems, which currently has two main drawbacks: 1) lack of standardization or bad performance of symmetric decryption under FHE; 2) lack of input data integrity. We report the first implementations of AES-GCM decryption under CKKS, which is the fastest implementation of standardized and commonly used symmetric encryption under homomorphic encryption that also provides integrity. Our solution opens the door to end-to-end implementations such as encrypted deep neural networks while relying on AES-GCM encrypted input.