NSHEDB：噪声敏感同态加密数据库查询引擎
NSHEDB: Noise-Sensitive Homomorphic Encrypted Database Query Engine
AI总结：
NSHEDB通过字级分层同态加密和噪声感知查询计划器，实现了高效安全的同态加密数据库查询，显著提升性能并减少存储需求。
摘要：
同态加密（HE）允许直接在加密数据上进行计算，为安全且隐私保护的数据存储和查询执行提供了强大的加密保障。然而，尽管其理论强大，HE在数据库系统中的实际应用仍然有限，因为极端的密文膨胀、内存开销以及启动时的计算成本限制了其使用。本文提出了NSHEDB，这是一个旨在从系统架构层面解决这些挑战的安全查询处理引擎。NSHEDB使用基于BFV方案的字级分层同态加密（LHE）以最小化密文膨胀并避免昂贵的启动过程。它引入了新的技术，用于使用纯同态计算执行相等性、范围和聚合操作，而无需在不同的HE方案（如CKKS/BFV/TFHE）之间转换密文或依赖受信任的硬件。此外，它还集成了一个噪声感知的查询计划器，以扩展计算深度同时保持安全保证。我们实现了并评估了NSHEDB在真实世界数据库工作负载（TPC-H）上的性能，并显示其在与最先进HE系统相比，实现了20x-V1370x的速度提升和73x的存储减少，同时在半诚实模型下保持128位的安全性，没有密钥泄露或受信任组件。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
