SaTC: CORE: Small: Collaborative: Oblivious ISAs for Secure and Efficient Enclave Programming

个人数据的计算对个人和社会都至关重要。例如，我们编写的程序可以预测早期发病的医疗状况，并在疾病成为流行病之前检测疾病的传播。然而，这种计算充满了隐私问题，因为程序及其运行的硬件会创建一系列线索，攻击者可以通过观察这些线索来重建个人数据，而无需直接看到数据。这个项目将创造出不留下任何线索的计算机系统，也就是说，没有可能泄露个人秘密的副作用。技术方法是引入一种新的遗忘指令集体系结构（OISA）来实现侧信道安全执行。oisa的关键思想是将编程模型与防止信息泄漏的具体技术解耦。第一个项目将研究一系列遗忘指令——从简单的遗忘指令，如遗忘条件移动或遗忘加载，到更复杂的指令，如遗忘排序或浮点操作——以提高性能。第二个项目推力将研究如何将这些指令中的每一个都移植到威胁模型中，例如，数字和电源侧通道。通过将威胁模型与编程模型分离，oisa将在软件和硬件方面开启创新。程序员可以专注于识别应用程序固有的秘密变量，同时抽象出微体系结构和威胁模型细节。硬件架构师可以专注于如何有效地保护这些秘密，以及如何在出现新威胁时修补现有实现。为了支持这一理念，该项目将培养一批新的学生和研究人员，他们可以跨电路、微架构、编译器和应用密码学工作，以构建安全系统，并在未来将学到的经验教训应用于需要跨层解决方案的其他高影响力问题。OISA项目将在面向公众的网站上存储所有出版物、代码和数据集，这些网站将在项目结束后的至少3年内由德克萨斯大学和伊利诺伊大学托管。这些信息将通过商业网站提供。这些网站的链接将在http://spark.ece.utexas.edu/oisa和http://cwfletcher.net/oisa.This上得到反映，该奖项反映了美国国家科学基金会的法定使命，并通过基金会的智力价值和更广泛的影响审查标准进行评估，认为值得支持。

Computing on personal data is critical for both personal and social good. For example, we write programs that predict early onset medical conditions and detect the spread of diseases before they become epidemics. However, such computing is fraught with privacy concerns because programs, and the hardware they run on, create a trail of clues that an attacker can observe to reconstruct personal data without ever seeing the data directly. This project will create computer systems that proactively leave no clues, i.e., no side-effects that can leak personal secrets.The technical approach is to introduce a new Oblivious Instruction Set Architecture (OISA) for side-channel secure execution. The key idea in OISAs is to decouple the programming model from the concrete techniques that prevent information leaks. The first project thrust will investigate a range of Oblivious instructions---from simple oblivious instructions like an oblivious conditional move or oblivious load to more complex instructions like oblivious sort or floating point operations---to improve performance. The second project thrust will investigate how each of these instructions can be ported across threat models, e.g., digital and power side channels.By decoupling threat model from programming model, OISAs will unlock innovation on both software and hardware fronts. Programmers can focus on identifying secret variables that are intrinsic to applications, while abstracting out micro-architecture and threat model details. Hardware architects can focus on how to efficiently protect those secrets, and how to patch existing implementations when new threats emerge. To support this philosophy, the project will train a new class of students and researchers who can work across circuits, micro-architecture, compilers and applied cryptography to build secure systems and, in the future, apply the lessons learned to other high-impact problems that require cross-layer solutions.The OISA project will store all publications, code, and data-sets on public-facing websites, hosted at both University of Texas and Illinois for at least 3 years after the end of the project. This information will be made available via commercial websites. Links to these websites will be mirrored at http://spark.ece.utexas.edu/oisa and http://cwfletcher.net/oisa.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.