IEEE J Biomed Health Inform. 2018 Mar;22(2):597-606. doi: 10.1109/JBHI.2017.2657458. Epub 2017 Jan 23.
Sharing the medical records of individuals among healthcare providers and researchers around the world can accelerate advances in medical research. While the idea seems increasingly practical due to cloud data services, maintaining patient privacy is of paramount importance. Standard encryption algorithms help protect sensitive data from outside attackers but they cannot be used to compute on this sensitive data while being encrypted. Homomorphic Encryption presents a very useful tool that can compute on encrypted data without the need to decrypt it. In this paper, we describe an optimized NTRU-based implementation of the GSW homomorphic encryption scheme. Our results show a factor of 58 × improvement in CPU performance compared to other recent work on encrypted medical data under the same security settings. Our system is built to be easily portable to GPUs resulting in an additional speedup of up to a factor of 104 × (and 410 ×) to offer an overall speedup of 6085 × (and 24011 ×) using a single GPU (or four GPUs), respectively.
在全球医疗服务提供者和研究人员之间共享个人医疗记录可以加速医学研究的进展。虽然由于云数据服务,这个想法似乎越来越可行,但维护患者隐私至关重要。标准的加密算法有助于保护敏感数据免受外部攻击者的攻击,但它们不能用于在加密数据上进行计算。同态加密提供了一种非常有用的工具,可以在不解密的情况下对加密数据进行计算。在本文中,我们描述了一种基于 NTRU 的 GSW 同态加密方案的优化实现。我们的结果表明,在相同的安全设置下,与其他最近关于加密医疗数据的工作相比,我们的 CPU 性能提高了 58 倍。我们的系统构建为易于移植到 GPU 上,从而分别提供高达 104 倍(和 410 倍)的额外加速,使用单个 GPU(或四个 GPU)提供 6085 倍(和 24011 倍)的整体加速。