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.

翻译：对机密数据进行隐私保护分析可以提升数据的价值，甚至改善人们的生活。全同态加密（FHE）能够实现隐私保护分析，但其计算开销巨大，且高效使用需要高度专业性。编译器可自动化参数配置和电路优化等环节，从而降低非密码学领域专家使用FHE的门槛。然而，多方场景仍存在复杂性，排除了许多有前景的应用案例，例如医疗研究中大规模健康记录的分析。代理重加密（PRE）技术允许将来自多个来源的数据转换为联合加密密钥，可支持FHE在多方场景中的应用。目前，尚不存在针对具有PRE能力的FHE的优化编译器。我们提出HElium，这是首个原生支持代理重加密的FHE优化编译器。HElium包含专为多方场景设计的领域特定语言（DSL）HEDSL。通过追踪加密密钥并在编译过程中转换计算电路，HElium能够最小化代价高昂的PRE操作次数。我们基于医疗研究中著名的肿瘤复发率实际案例评估了HElium的优化效果。实证评估表明，HElium显著降低了复杂PRE操作引入的开销，且随着输入数据量的增加，这种优化效果更为显著。