An Implementation of Private Function Evaluation Using FHE and TEE for Smart Computing Systems

Ruixiao Li, Ryutaro Onishi, Hayato Yamana

Abstract: To protect sensitive data in cloud outsourcing smart systems, we implemented a private function evaluation system with fully homomorphic encryption (FHE) and trusted execution environment (TEE) using lookup tables (LUT), which preserves the privacy of data in various smart systems, including anomaly detection in smart grids. The proposed system introduces a trusted authority (TA) to manage FHE keys and generate private information retrieval (PIR) queries to extract the output from the LUT. The remaining problem in our previous work is that the TA knows the index distribution of data points in LUTs and the index of matched data points, which may cause security issues. In this work, we solve the security issues by executing operations in the TA with the TEE and reducing the runtime using unencrypted LUTs. Our system allows the computation of arbitrary multi-input functions to improve efficiency and expand the scope of applications with FHE in smart systems. We confirmed the evaluation runtime of an 18-bit one-input function needs 2.49 s. Compared to our previous work, our system achieved 2.1x speed up for an 8-bit three-input function with one thread.