Abstract: With the rapid development of the digital economy, efficiently utilizing data while preserving privacy has become a critical challenge in modern technological advancement. Privacy computing, as a critical technical framework to address the contradiction between data availability and invisibility, is gradually transitioning from theory to practical application. Among its core technologies, homomorphic encryption, zeroknowledge proofs, and secure multiparty computation have made significant progress in both theoretical development and engineering implementation, demonstrating broad applicability in highperformance computing environments. This paper presents a comprehensive review of these three categories of highperformance encryption algorithms, focusing on their research progress and analyzing them across three dimensions: computational efficiency, communication overhead, and adaptability to highperformance computing environments. The analysis results indicate that homomorphic encryption is wellsuited for noninteractive data processing tasks with strong autonomy, although it incurs high computational and communication costs; zeroknowledge proofs exhibit high verification efficiency, making them suitable for highconcurrency scenarios, but still face performance bottlenecks in proof generation; secure multiparty computation excels in multiparty collaborative computing and has recently become feasible for deployment through protocol optimization and hardware support. This paper compares the performance and applicability of these algorithms, and explores future research directions, including the dynamic balance between generality and specialization of algorithms, as well as the multidimensional tradeoffs among performance, security, and interpretability, providing guidance for the future design and deployment of highperformance encryption algorithms.

Key words: privacy computing, highperformance encryption algorithm, homomorphic encryption, zeroknowledge proof, secure multiparty computation

摘要： 在数字经济快速发展的背景下，如何在保障数据隐私的前提下高效利用数据成为当前科技发展的核心挑战.隐私计算作为解决“数据可用不可见”问题的关键技术体系逐步走向实际应用.其中，同态加密、零知识证明和安全多方计算作为3大核心加密技术，在理论构建与工程实现方面取得了显著进展，并在高性能计算环境中展现出广泛应用潜力.围绕上述3类高性能加密算法展开系统综述，介绍算法研究进展，并重点从计算效率、通信开销与高性能计算环境适配性3个维度进行分析.结果表明：同态加密适用于无需交互的数据处理任务，具备较强的自治性，但计算与通信开销较高；零知识证明在验证效率上表现突出，适合高并发验证场景，但证明生成仍面临性能瓶颈；安全多方计算在多机构协作计算中优势明显，近年通过协议优化与硬件协同实现了工程部署可行性.另外，对3类算法的性能和适用场景进行对比分析，并对未来研究中算法通用性与专用性的动态平衡以及性能、安全与可解释性的多维权衡进行了展望，为后续高性能加密算法设计与应用部署提供参考.

关键词: 隐私计算, 高性能加密算法, 同态加密, 零知识证明, 安全多方计算