The Alliance of HE and TEE to Enhance their Performance and Security

S. D'Antonio, Giannis Lazarou, Giovanni Mazzeo, Oana Stan, Martin Zuber, Ioannis Tsavdaridis
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引用次数: 0

Abstract

While protection of data at-rest and data in-transit can be achieved using standard algorithms and technologies, the protection of data in-use is still, to a large extent, an open issue. Homomorphic Encryption (HE) and Trusted Execution Environment (TEE) are among the most popular approaches to shield computations. The former ensures high security guarantees but it suffers from a significant overhead. The latter, instead, provides lower execution time but it is affected by security drawbacks. In this paper, we propose SOTERIA, a privacy-preserving computation solution that combines HE and TEE to mitigate their limitations. The approach foresees the execution of sensitive processing with homomorphic encryption and the usage of a TEE to perform switches between different homomorphic cryptosystems. In fact, there are different kinds of computation algorithms where the co-existence of linear and non-linear functions makes the HE-based processing even more onerous. SOTERIA is developed in the context of the ENCRYPT project and will be validated in a use case of financial data processing.
高等教育学院与TEE的联盟,以提高其性能和安全性
虽然可以使用标准算法和技术来保护静态数据和传输中的数据,但在很大程度上,保护使用中的数据仍然是一个悬而未决的问题。同态加密(HE)和可信执行环境(TEE)是屏蔽计算中最流行的方法。前者保证了高安全性,但开销很大。后者提供较短的执行时间,但受到安全性缺陷的影响。在本文中,我们提出了SOTERIA,一种结合HE和TEE以减轻其局限性的隐私保护计算解决方案。该方法预见到使用同态加密执行敏感处理,并使用TEE在不同同态密码系统之间执行切换。事实上,在许多不同类型的计算算法中,线性和非线性函数的共存使得基于he的处理更加繁重。SOTERIA是在ENCRYPT项目的背景下开发的,并将在金融数据处理的用例中进行验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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