# Keystone: An Open Framework for Architecting TEEs

arXiv: https://arxiv.org/abs/1907.10119 · HTML: https://mlsanity.com/paper/1907.10119/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jul 2019.

## Built on by (most cited first, 1 of 1)

- [Obsidian: Cooperative State-Space Exploration for Performant Inference on Secure ML Accelerators](https://mlsanity.com/paper/2409.02817/) (2024)

## Abstract (arXiv)

Trusted execution environments (TEEs) are being used in all the devices from embedded sensors to cloud servers and encompass a range of cost, power constraints, and security threat model choices. On the other hand, each of the current vendor-specific TEEs makes a fixed set of trade-offs with little room for customization. We present Keystone -- the first open-source framework for building customized TEEs. Keystone uses simple abstractions provided by the hardware such as memory isolation and a programmable layer underneath untrusted components (e.g., OS). We build reusable TEE core primitives from these abstractions while allowing platform-specific modifications and application features. We showcase how Keystone-based TEEs run on unmodified RISC-V hardware and demonstrate the strengths of our design in terms of security, TCB size, execution of a range of benchmarks, applications, kernels, and deployment models.