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

TL;DR

Arca introduces a lightweight, TEE-in-Container architecture for cloud-native workloads that enhances security, reduces overhead, and maintains high performance by isolating each workload in independent trust domains.

Contribution

The paper proposes a novel TEE-in-Container design that isolates workloads, minimizes TCB, and improves security and performance over existing container-in-TEE solutions.

Findings

Achieves near-native performance on multiple TEE platforms.

Outperforms existing CoCo framework in benchmarks.

Significantly reduces TCB, enhancing verifiability and resilience.

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.