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arXiv · 2412.03842

CCxTrust: Confidential Computing Platform Based on TEE and TPM Collaborative Trust

Ketong Shang·Jiangnan Lin·Yu Qin·Muyan Shen·Hongzhan Ma·Wei Feng·Dengguo Feng
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Abstract

Confidential Computing has emerged to address data security challenges in cloud-centric deployments by protecting data in use through hardware-level isolation. However, reliance on a single hardware root of trust (RoT) limits user confidence in cloud platforms, especially for high-performance AI services, where end-to-end protection of sensitive models and data is critical. Furthermore, the lack of interoperability and a unified trust model in multi-cloud environments prevents the establishment of a cross-platform, cross-cloud chain of trust, creating a significant trust gap for users with high privacy requirements. To address the challenges mentioned above, this paper proposes CCxTrust (Confidential Computing with Trust), a confidential computing platform leveraging collaborative roots of trust from TEE and TPM. CCxTrust combines the black-box RoT embedded in the CPU-TEE with the flexible white-box RoT of TPM to establish a collaborative trust framework. The platform implements independent Roots of Trust for Measurement (RTM) for TEE and TPM, and a collaborative Root of Trust for Report (RTR) for composite attestation. The Root of Trust for Storage (RTS) is solely supported by TPM. We also present the design and implementation of a confidential TPM supporting multiple modes for secure use within confidential virtual machines. Additionally, we propose a composite attestation protocol integrating TEE and TPM to enhance security and attestation efficiency, which is proven secure under the PCL protocol security model. We implemented a prototype of CCxTrust on a confidential computing server with AMD SEV-SNP and TPM chips, requiring minimal modifications to the TPM and guest Linux kernel. The composite attestation efficiency improved by 24% without significant overhead, while Confidential TPM performance showed a 16.47% reduction compared to standard TPM.

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Ketong Shang, Jiangnan Lin, Yu Qin, Muyan Shen, Hongzhan Ma, Wei Feng, Dengguo Feng. 2024-12-12. CCxTrust: Confidential Computing Platform Based on TEE and TPM Collaborative Trust. https://arxiv.org/abs/2412.03842

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