Reducing the Price of Protection: Identifying and Migrating Non-Sensitive Code in TEE

Yin Liu, E. Tilevich
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Abstract

As the trusted computing base (TCB) unnecessarily increases its size, the performance and security of Trusted Execution Environments (TEE) can deteriorate rapidly. Existing solutions focus on placing only the necessary program parts in TEE, but neglect the numerous cases of legacy software with misplaced TEE-based non-sensitive code. In this paper, we introduce a new type of software refactoring—TEE Insourcing—that identifies and migrates non-sensitive code out of TEE. We present TEE-DRUP, the first semi-automated TEE Insourcing framework whose process comprises two phases: (1) a variable sensitivity analysis designates each variable as sensitive or non-sensitive; (2) a compiler-assisted program transformation automatically moves the functions that never operate on the sensitive variables out of TEE. Developers can participate to verify and confirm sensitive variables, and specify additional non-sensitive functions to migrate. The evaluation results of TEE-DRUP on real-world programs are encouraging. TEE-DRUP distinguishes between sensitive and non-sensitive variables with satisfactory accuracy, precision, and recall — all of their actual values are greater than 80% in the majority of evaluation scenarios. Further, moving non-sensitive code out of TEE improves system performance, with the speedup ranging between 1.35 and 10K. Finally, TEE-DRUP's automated program transformation requires only a small programming effort.
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降低保护的代价:在TEE中识别和迁移非敏感代码
随着可信计算基础(TCB)规模的不必要增加,可信执行环境(TEE)的性能和安全性会迅速恶化。现有的解决方案只关注于在TEE中放置必要的程序部分,而忽略了遗留软件中基于TEE的非敏感代码的大量情况。在本文中,我们介绍了一种新的软件重构——TEE内建——它可以识别和迁移TEE外的非敏感代码。我们提出TEE- drup,第一个半自动化TEE内包框架,其过程包括两个阶段:(1)变量敏感性分析指定每个变量为敏感或非敏感;(2)编译器辅助的程序转换自动将从不操作敏感变量的函数移出TEE。开发人员可以参与验证和确认敏感变量,并指定要迁移的其他非敏感函数。TEE-DRUP对实际项目的评价结果令人鼓舞。TEE-DRUP区分敏感变量和非敏感变量,具有令人满意的准确度、精密度和召回率——在大多数评估场景中,它们的实际值都大于80%。此外,将非敏感代码移出TEE可以提高系统性能,加速范围在1.35到10K之间。最后,TEE-DRUP的自动化程序转换只需要很小的编程工作。
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