Toward Scalable Fully Homomorphic Encryption Through Light Trusted Computing Assistance
This addresses the problem of scalable secure outsourcing of computation for users needing confidentiality and integrity, though it is incremental as it builds on existing FHE and TEE technologies.
The paper tackles the performance slowdown in fully homomorphic encryption (FHE) by proposing TEEFHE, a hybrid system that uses hardware Trusted Execution Environments (TEEs) like SGX to assist FHE, specifically moving the bootstrapping step to a secured enclave, resulting in improved time and space efficiency compared to software-only FHE schemes.
It has been a long standing problem to securely outsource computation tasks to an untrusted party with integrity and confidentiality guarantees. While fully homomorphic encryption (FHE) is a promising technique that allows computations performed on the encrypted data, it suffers from a significant slow down to the computation. In this paper we propose a hybrid solution that uses the latest hardware Trusted Execution Environments (TEEs) to assist FHE by moving the bootstrapping step, which is one of the major obstacles in designing practical FHE schemes, to a secured SGX enclave. TEEFHE, the hybrid system we designed, makes it possible for homomorphic computations to be performed on smaller ciphertext and secret key, providing better performance and lower memory consumption. We make an effort to mitigate side channel leakages within SGX by making the memory access patterns totally independent from the secret information. The evaluation shows that TEEFHE effectively improves the software only FHE schemes in terms of both time and space.