TWC: Small: Towards Practical Fully Homomorphic Encryption

TWC：小：迈向实用的全同态加密

• 批准号: 1319130
• 负责人: Berk Sunar
• 金额: $ 49.98万
• 依托单位: Worcester Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1319130&HistoricalAwards=false
• 关键词: TWC; Small; Towards; Practical; Fully

Fully homomorphic encryption (FHE) allows an untrusted party to efficiently compute any compact function directly on ciphertexts. When made available over an untrusted cloud server, data is submitted and returned in encrypted form, and the execution remains secure against malicious users. Early FHE proposals had rather disappointing efficiencies. Recently new FHE schemes based on the difficulty of the learning with errors (LWE) problem emerged with orders of magnitude improvement over earlier constructions. This project addresses a variety of problems in engineering, computer science and mathematics all centered around the goal of bringing LWE-based homomorphic encryption techniques closer to practice which could impact the way society utilizes computing services.The project team explores three research components. The first research component investigates algorithmic optimizations to speed up LWE-based schemes, and to develop optimized software implementations on CPUs and graphics processing units. Specifically, the investigators apply optimization techniques including changing the representation of the operands, batching, and precomputation. The team also aims to build a LWE-FHE based homomorphic instruction set. In another research component the project team develops application specific custom hardware to overcome inefficiencies of software platforms. Finally, we investigate the customization of parameters to match the needs of select lightweight cryptographic primitives.

全同态加密（FHE）允许不可信方直接在密文上有效地计算任何紧致函数。 当在不受信任的云服务器上可用时，数据以加密的形式提交和返回，并且执行仍然安全，不受恶意用户的攻击。早期的FHE提案效率相当令人失望。 最近，基于错误学习（LWE）问题难度的新FHE方案出现，比早期的构造有了几个数量级的改进。该项目解决了工程、计算机科学和数学领域的各种问题，所有这些问题都围绕着将基于LWE的同态加密技术更接近实践的目标，这可能会影响社会利用计算服务的方式。项目团队探索了三个研究组成部分。第一个研究部分研究算法优化，以加快基于LWE的方案，并开发优化的软件实现CPU和图形处理单元。具体来说，研究人员应用优化技术，包括改变操作数的表示，迭代和预计算。该团队还旨在构建一个基于LWE-FHE的同态指令集。在另一项研究中，项目团队开发了特定于应用的定制硬件，以克服软件平台的效率低下。最后，我们调查的定制参数，以满足选择轻量级密码原语的需求。