Arca: A Lightweight Confidential Container Architecture for Cloud-Native Environments

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Authors: Di Lu, Mengna Sun, Qingwen Zhang, Yujia Liu, Jia Zhang, Xuewen Dong, Yulong Shen, Jianfeng Ma
Cited by: 0

Abstract

Confidential containers protect cloud-native workloads using trusted execution environments (TEEs). However, existing Container-in-TEE designs (e.g., Confidential Containers (CoCo)) encapsulate the entire runtime within the TEE, inflating the trusted computing base (TCB) and introducing redundant components and cross-layer overhead. We present Arca, a lightweight confidential container framework based on a TEE-in-Container architecture that isolates each workload in an independent, hardware-enforced trust domain while keeping orchestration logic outside the TEE. This design minimizes inter-layer dependencies, confines compromise to per-container boundaries, and restores the TEE's minimal trust principle. We implemented Arca on Intel SGX, Intel TDX, and AMD SEV. Experimental results show that Arca achieves near-native performance and outperforms CoCo in most benchmarks, while the reduced TCB significantly improves verifiability and resilience against host-level compromise. Arca emonstrates that efficient container management and strong runtime confidentiality can be achieved without sacrificing security assurance.

Fields of Study & Subjects

Security and Verification in Computing Cloud Computing and Resource Management Cloud Data Security Solutions

Publication details

Journal / source
arXiv (Cornell University)
Publication date
3 January 2026
Document type
Preprint