TEEMon：一个用于TEE的持续性能监控框架
TEEMon: A continuous performance monitoring framework for TEEs
摘要：
可信执行环境（TEE），如英特尔Software Guard eXtensions（SGX），被认为是解决云安全挑战的一种有前途的方法。TEE通过提供一个隔离的安全存储区，即，飞地安全性保证由CPU提供，因此即使系统软件受到危害，攻击者也永远无法访问安全区的内容。虽然这种方法确保了应用程序的强大安全性保证，但它也引入了相当大的运行时开销，部分原因是受保护内存（飞地页面缓存）的可用性有限。目前，只有数量有限的基于TEE的应用程序的性能测量工具存在，没有提供在运行时的性能监控和分析。本文介绍了TEEMon，第一个连续的性能监测和分析工具，基于TEE的应用程序。TEEMon不仅在运行时提供细粒度的性能指标，而且还帮助分析识别性能瓶颈的原因，例如，过多的系统调用。我们的方法与现有的开源工具（例如，Prometheus或Grafana）提供了一个整体监控解决方案，特别针对通过Docker容器或Kubernetes部署的系统进行了优化，并提供了几个专用的指标和可视化。我们的评估表明，TEEMon的开销范围从5%到17%。
英文摘要：
Trusted Execution Environments (TEEs), such as Intel Software Guard eXtensions (SGX), are considered as a promising approach to resolve security challenges in clouds. TEEs protect the confidentiality and integrity of application code and data even against privileged attackers with root and physical access by providing an isolated secure memory area, i.e., enclaves. The security guarantees are provided by the CPU, thus even if system software is compromised, the attacker can never access the enclave's content. While this approach ensures strong security guarantees for applications, it also introduces a considerable runtime overhead in part by the limited availability of protected memory (enclave page cache). Currently, only a limited number of performance measurement tools for TEE-based applications exist and none offer performance monitoring and analysis during runtime. This paper presents TEEMon, the first continuous performance monitoring and analysis tool for TEE-based applications. TEEMon provides not only fine-grained performance metrics during runtime, but also assists the analysis of identifying causes of performance bottlenecks, e.g., excessive system calls. Our approach smoothly integrates with existing open-source tools (e.g., Prometheus or Grafana) towards a holistic monitoring solution, particularly optimized for systems deployed through Docker containers or Kubernetes and offers several dedicated metrics and visualizations. Our evaluation shows that TEEMon's overhead ranges from 5% to 17%.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
