SaTC: STARSS: Small: Collaborative: Design and Security Verification of Next-Generation Open-Source Processors

SaTC：STARSS：小型：协作：下一代开源处理器的设计和安全验证

• 批准号: 1814190
• 负责人: Ruby Lee
• 金额: $ 16.56万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1814190&HistoricalAwards=false
• 关键词: SaTC; STARSS; Small; Collaborative; Design

This project will develop new open-source processor architectures with advanced security features. The security features will be added to existing open-source processors to help protect the confidentiality and integrity of data and to protect against side-channel attacks. Beyond the design, the project will also provide new methodology to verify the proposed security feature, to provide assurance that the processor hardware itself is provably secure. The first thrust of the project focuses on side-channel protections, especially of processor caches, and other functional units that can be exploited to leak secret information. It further adds security counters and new means to protect trusted software modules. The second thrust focuses on the design of the security verification approaches for hardware, including the use of satisfiability modulo theories (SMT) based solvers and temporal logics.If successful, this will make open-source processors and their applications more secure against attacks. It will enable the academic community to further develop and extend the capabilities of the ope-source secure processor and further education in hardware security.All artefacts developed by this project will be available online at http://caslab.csl.yale.edu/code/ or http://palms.ee.princeton.edu. The web sites will be maintained for the duration of the project and as long as the research groups involved in this project are active.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.

该项目将开发具有高级安全功能的新开源处理器体系结构。安全功能将添加到现有的开源处理器中，以帮助保护数据的机密性和完整性并保护侧通道攻击。除了设计外，该项目还将提供新的方法来验证所提出的安全功能，以确保处理器硬件本身是安全的。该项目的第一个推力集中在侧通道保护措施上，尤其是处理器缓存和其他可以利用以泄漏秘密信息的功能单元。它进一步添加了安全柜台和保护信任软件模块的新方法。第二个推力着重于硬件安全验证方法的设计，包括使用基于满意的模型理论（SMT）的求解器和时间逻辑。这将使学术界能够进一步开发和扩展OPE源安全处理器的功能和硬件安全性的进一步教育。该项目开发的所有文物将在http://caslab.csl.csl.yale.edu/code/code/或http://palms.ee.princeton.edu.u.eedu/code/或该网站将在项目的期限内维持，只要参与该项目的研究小组很活跃。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响评估标准，被认为值得通过评估来提供支持。

项目成果

Speculative Execution Attacks and Hardware Defenses

推测执行攻击和硬件防御

• DOI: 10.1145/3474376.3487404
• 发表时间: 2021
• 期刊: ASHES '21: Proceedings of the 5th Workshop on Attacks and Solutions in Hardware Security
• 作者: Lee, Ruby B.

Power-Grid Controller Anomaly Detection with Enhanced Temporal Deep Learning

• DOI: 10.1109/trustcom/bigdatase.2019.00030
• 发表时间: 2018-06
• 期刊: 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
• 作者: Zecheng He;Aswin Raghavan;Guangyuan Hu;S. Chai;Ruby B. Lee

Sensitive-Sample Fingerprinting of Deep Neural Networks

• DOI: 10.1109/cvpr.2019.00486
• 发表时间: 2019-06
• 期刊: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
• 作者: Zecheng He;Tianwei Zhang;R. Lee

Analyzing Cache Side Channels Using Deep Neural Networks

• DOI: 10.1145/3274694.3274715
• 发表时间: 2018-12
• 期刊: Proceedings of the 34th Annual Computer Security Applications Conference
• 作者: Tianwei Zhang;Yinqian Zhang;R. Lee

Position Paper: Consider Hardware-enhanced Defenses for Rootkit Attacks

• DOI: 10.1145/3458903.3458909
• 发表时间: 2020-10
• 期刊: Hardware and Architectural Support for Security and Privacy
• 作者: Guangyuan Hu;Tianwei Zhang;Ruby B. Lee