ACAI: Protecting Accelerator Execution with Arm Confidential Computing Architecture

Authors: 

Supraja Sridhara, Andrin Bertschi, Benedict Schl├╝ter, Mark Kuhne, Fabio Aliberti, and Shweta Shinde, ETH Zurich

Abstract: 

Trusted execution environments in several existing and upcoming CPUs demonstrate the success of confidential computing, with the caveat that tenants cannot securely use accelerators such as GPUs and FPGAs. In this paper, we reconsider the Arm Confidential Computing Architecture (CCA) design, an upcoming TEE feature in Armv9-A, to address this gap. We observe that CCA offers the right abstraction and mechanisms to allow confidential VMs to use accelerators as a first-class abstraction. We build ACAI, a CCA-based solution, with a principled approach of extending CCA security invariants to device-side access to address several critical security gaps. Our experimental results on GPU and FPGA demonstrate the feasibility of ACAI while maintaining security guarantees.

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