PubSub-SGX: Exploiting Trusted Execution Environments for Privacy-Preserving Publish/Subscribe Systems

Sergei Arnautov, Andrey Brito, P. Felber, C. Fetzer, Franz Gregor, R. Krahn, W. Ożga, André Martin, V. Schiavoni, Fábio Silva, Marcus Tenorio, Nikolaus Thummel
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引用次数: 15

Abstract

This paper presents PUBSUB-SGX, a content-based publish-subscribe system that exploits trusted execution environments (TEEs), such as Intel SGX, to guarantee confidentiality and integrity of data as well as anonymity and privacy of publishers and subscribers. We describe the technical details of our Python implementation, as well as the required system support introduced to deploy our system in a container-based runtime. Our evaluation results show that our approach is sound, while at the same time highlighting the performance and scalability trade-offs. In particular, by supporting just-in-time compilation inside of TEEs, Python programs inside of TEEs are in general faster than when executed natively using standard CPython.
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PubSub-SGX:利用可信执行环境保护隐私发布/订阅系统
本文提出了一种基于内容的发布-订阅系统PUBSUB-SGX,该系统利用可信执行环境(tee),如Intel SGX,来保证数据的机密性和完整性以及发布者和订阅者的匿名性和隐私性。我们描述了Python实现的技术细节,以及在基于容器的运行时中部署系统所需的系统支持。我们的评估结果表明,我们的方法是合理的,同时突出了性能和可伸缩性的权衡。特别是,通过支持TEEs内部的即时编译,TEEs内部的Python程序通常比使用标准CPython本地执行时要快。
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