Building a lightweight trusted execution environment for Arm GPUs

Abstract

A wide range of Arm endpoints leverage integrated and discrete GPUs to accelerate computation. However, Arm GPU security has not been explored by the community. Existing work has used Trusted Execution Environments (TEEs) to address GPU security concerns on Intel-based platforms, but there are numerous architectural differences that lead to novel technical challenges in deploying TEEs for Arm GPUs. There is a need for generalizable and efficient Arm-based GPU security mechanisms. To address these problems, we present StrongBox , the first GPU TEE for secured general computation on Arm endpoints. StrongBox provides an isolated execution environment by ensuring exclusive access to GPU. Our approach is based in part on a dynamic, fine-grained memory protection policy as Arm-based GPUs typically share a unified memory with the CPU. Furthermore, StrongBox reduces runtime overhead from the redundant security introspection operations. We also design an effective defense mechanism within secure world to protect the confidential GPU computation. Our design leverages the widely-deployed Arm TrustZone and generic Arm features, without hardware modification or architectural changes. We prototype StrongBox using an off-the-shelf Arm Mali GPU and perform an extensive evaluation. Results show that StrongBox successfully ensures GPU computation security with a low (4.70%–15.26%) overhead.