Scalable Memory Protection in the PENGLAI Enclave

Authors: 

Erhu Feng, Xu Lu, Dong Du, Bicheng Yang, and Xueqiang Jiang, Institute of Parallel and Distributed Systems, Shanghai Jiao Tong University; Engineering Research Center for Domain-specific Operating Systems, Ministry of Education, China; Yubin Xia, Binyu Zang, and Haibo Chen, Institute of Parallel and Distributed Systems, Shanghai Jiao Tong University; Shanghai AI Laboratory; Engineering Research Center for Domain-specific Operating Systems, Ministry of Education, China

Abstract: 

Secure hardware enclaves have been widely used for protecting security-critical applications in the cloud. However, existing enclave designs fail to meet the requirements of scalability demanded by new scenarios like serverless computing, mainly due to the limitations in their secure memory protection mechanisms, including static allocation, restricted capacity and high-cost initialization. In this paper, we propose a software-hardware co-design to support dynamic, fine-grained, large-scale secure memory as well as fast-initialization. We first introduce two new hardware primitives: 1) Guarded Page Table (GPT), which protects page table pages to support page-level secure memory isolation; 2) Mountable Merkle Tree (MMT), which supports scalable integrity protection for secure memory. Upon these two primitives, our system can scale to thousands of concurrent enclaves with high resource utilization and eliminate the high-cost initialization of secure memory using fork-style enclave creation without weakening the security guarantees.

We have implemented a prototype of our design based on Penglai, an open-sourced enclave system for RISC-V. The experimental results show that Penglai can support 1,000s enclave instances running concurrently and scale up to 512GB secure memory with both encryption and integrity protection. The overhead of GPT is 5% for memory-intensive workloads (e.g., Redis) and negligible for CPU-intensive workloads (e.g., RV8 and Coremarks). Penglai also reduces the latency of secure memory initialization by three orders of magnitude and gains 3.6x speedup for real-world applications (e.g., MapReduce).

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BibTeX
@inproceedings {273705,
author = {Erhu Feng and Xu Lu and Dong Du and Bicheng Yang and Xueqiang Jiang and Yubin Xia and Binyu Zang and Haibo Chen},
title = {Scalable Memory Protection in the {PENGLAI} Enclave},
booktitle = {15th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 21)},
year = {2021},
isbn = {978-1-939133-22-9},
pages = {275--294},
url = {https://www.usenix.org/conference/osdi21/presentation/feng},
publisher = {{USENIX} Association},
month = jul,
}