HElium: A Language and Compiler for Fully Homomorphic Encryption with Support for Proxy Re-Encryption

TL;DR

HElium is an innovative compiler that optimizes fully homomorphic encryption with proxy re-encryption support, enabling efficient multi-party privacy-preserving data analysis, especially in medical research contexts.

Contribution

It introduces HElium, the first FHE compiler with native proxy re-encryption support and a specialized DSL for multi-party scenarios, reducing computational overhead.

Findings

Significantly reduces overhead of proxy re-encryption operations.

Effectively handles large-scale multi-party data analysis.

Improves feasibility of privacy-preserving medical research.

Abstract

Privacy-preserving analysis of confidential data can increase the value of such data and even improve peoples' lives. Fully homomorphic encryption (FHE) can enable privacy-preserving analysis. However, FHE adds a large amount of computational overhead and its efficient use requires a high level of expertise. Compilers can automate certain aspects such as parameterization and circuit optimizations. This in turn makes FHE accessible to non-cryptographers. Yet, multi-party scenarios remain complicated and exclude many promising use cases such as analyses of large amounts of health records for medical research. Proxy re-encryption (PRE), a technique that allows the conversion of data from multiple sources to a joint encryption key, can enable FHE for multi-party scenarios. Today, there are no optimizing compilers for FHE with PRE capabilities. We propose HElium, the first optimizing FHE compiler with native support for proxy re-encryption. HElium features HEDSL, a domain-specific language (DSL) specifically designed for multi-party scenarios. By tracking encryption keys and transforming the computation circuit during compilation, HElium minimizes the number of expensive PRE operations. We evaluate the effectiveness of HElium's optimizations based on the real-world use case of the tumor recurrence rate, a well-known subject of medical research. Our empirical evaluation shows that HElium substantially reduces the overhead introduced through complex PRE operations, an effect that increases for larger amounts of input data.