使用小型TCB安全的太量级数据处理

Bruno Vavala, N. Neves, P. Steenkiste
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引用次数: 4

摘要

将服务外包给第三方提供商需要付出很高的安全成本——要完全信任提供商。使用可信硬件会有所帮助,但是当前的可信执行环境不能充分支持处理大规模数据集的服务。我们提出了LAST-GT,这是一个通过支持在大状态上执行自包含服务的系统,它具有小型和通用的可信计算基础(TCB),从而弥合了这一差距。LAST-GT使用广泛部署的可信硬件来保证远程平台上执行的完整性和可验证性,并通过基于虚拟内存的简单技术安全地向服务提供数据。因此,LAST-GT是通用的,适用于许多场景,例如计算基因组学和数据库,正如我们在基于安全管理程序上的LAST-GT实现的实验评估中所示。我们还描述了在Intel SGX上的可能实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Secure Tera-scale Data Crunching with a Small TCB
Outsourcing services to third-party providers comes with a high security cost—to fully trust the providers. Using trusted hardware can help, but current trusted execution environments do not adequately support services that process very large scale datasets. We present LAST-GT, a system that bridges this gap by supporting the execution of self-contained services over a large state, with a small and generic trusted computing base (TCB). LAST-GT uses widely deployed trusted hardware to guarantee integrity and verifiability of the execution on a remote platform, and it securely supplies data to the service through simple techniques based on virtual memory. As a result, LAST-GT is general and applicable to many scenarios such as computational genomics and databases, as we show in our experimental evaluation based on an implementation of LAST-GT on a secure hypervisor. We also describe a possible implementation on Intel SGX.
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