Caihua Li (Yale University), Seung-seob Lee (Yale University), Lin Zhong (Yale University)

Confidential Computing (CC) has received increasing attention in recent years as a mechanism to protect user data from untrusted operating systems (OSes). Existing CC solutions hide confidential memory from the OS and/or encrypt it to achieve confidentiality. In doing so, they render OS memory optimization unusable or complicate the trusted computing base (TCB) required for optimization. This paper presents our results toward overcoming these limitations, synthesized in a CC design named Blindfold. Like many other CC solutions, Blindfold relies on a small trusted software component running at a higher privilege level than the kernel, called Guardian. It features three techniques that can enhance existing CC solutions. First, instead of nesting page tables, Blindfold’s Guardian mediates how the OS accesses memory and handles exceptions by switching page and interrupt tables. Second, Blindfold employs a lightweight capability system to regulate the OS’s semantic access to user memory, unifying case-by-case approaches in previous work. Finally, Blindfold provides carefully designed secure ABI for confidential memory management without encryption. We report an implementation of Blindfold that works on ARMv8-A/Linux. Using Blindfold's prototype, we are able to evaluate the cost of enabling confidential memory management by the untrusted Linux kernel. We show Blindfold has a smaller runtime TCB than related systems and enjoys competitive performance. More importantly, we show that the Linux kernel, including all of its memory optimizations except memory compression, can function properly for confidential memory. This requires only about 400 lines of kernel modifications.

View More Papers

User Comprehension and Comfort with Eye-Tracking and Hand-Tracking Permissions...

Kaiming Cheng (University of Washington), Mattea Sim (Indiana University), Tadayoshi Kohno (University of Washington), Franziska Roesner (University of Washington)

Read More

Silence False Alarms: Identifying Anti-Reentrancy Patterns on Ethereum to...

Qiyang Song (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences), Heqing Huang (Institute of Information Engineering, Chinese Academy of Sciences), Xiaoqi Jia (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences), Yuanbo Xie (Institute of Information…

Read More

GhostShot: Manipulating the Image of CCD Cameras with Electromagnetic...

Yanze Ren (Zhejiang University), Qinhong Jiang (Zhejiang University), Chen Yan (Zhejiang University), Xiaoyu Ji (Zhejiang University), Wenyuan Xu (Zhejiang University)

Read More