Homomorphic encryption (HE) enables computations directly on encrypted data, offering strong cryptographic guarantees for secure and privacy-preserving data storage and query execution. However, despite its theoretical power, practical adoption of HE in database systems remains limited due to extreme cipher-text expansion, memory overhead, and the computational cost of bootstrapping, which resets noise levels for correctness. This paper presents NSHEDB, a secure query processing engine designed to address these challenges at the system architecture level. NSHEDB uses word-level leveled HE (LHE) based on the BFV scheme to minimize ciphertext expansion and avoid costly bootstrapping. It introduces novel techniques for executing equality, range, and aggregation operations using purely homomorphic computation, without transciphering between different HE schemes (e.g., CKKS/BFV/TFHE) or relying on trusted hardware. Additionally, it incorporates a noise-aware query planner to extend computation depth while preserving security guarantees. We implement and evaluate NSHEDB on real-world database workloads (TPC-H) and show that it achieves 20x-V1370x speedup and a 73x storage reduction compared to state-of-the-art HE-based systems, while upholding 128-bit security in a semi-honest model with no key release or trusted components.

翻译：同态加密（HE）允许直接在加密数据上进行计算，为安全且保护隐私的数据存储与查询执行提供了强大的密码学保证。然而，尽管其理论能力强大，但由于极端的密文膨胀、内存开销以及用于重置噪声以保证正确性的自举操作带来的计算成本，HE在数据库系统中的实际应用仍然有限。本文提出了NSHEDB，一种在系统架构层面应对这些挑战的安全查询处理引擎。NSHEDB采用基于BFV方案的词级分层同态加密（LHE）来最小化密文膨胀并避免昂贵的自举操作。它引入了新颖的技术，用于执行相等、范围和聚合操作，这些操作完全基于同态计算，无需在不同HE方案（例如CKKS/BFV/TFHE）之间进行密文转换，也不依赖于可信硬件。此外，它集成了一个噪声感知查询规划器，以在保持安全保证的同时扩展计算深度。我们在真实数据库工作负载（TPC-H）上实现并评估了NSHEDB，结果表明，与最先进的基于HE的系统相比，它在半诚实模型下（无需密钥释放或可信组件）实现了20倍至1370倍的加速以及73倍的存储减少，同时维持了128位的安全级别。