Towards Efficient and Practical Multi-party Computation under Inconsistent Trust in TEEs
Xuanwei Hu, Rujia Li, Yi Liu, Qi Wang
Abstract
Secure multi-party computation (MPC) allows joint computations on sensitive data while guaranteeing privacy and correctness. In recent years, a series of MPC protocols assisted by trusted execution environments (TEEs) have been proposed to reduce overhead brought by costly cryptographic techniques. However, existing protocols either generally assume consistent trust in TEEs among all participating parties, or require dedicated designs for different applications. This prevents the protocols from being deployed in practice. To address these challenges, in this work, we propose a generic MPC protocol without assuming consistent trust in TEEs while fully utilizing heterogeneous TEEs to improve efficiency. To this end, we propose a security model to capture parties' inconsistent trust in TEEs and prove the security of our protocol under a simpler variant of the UC framework (SUC framework). In addition, we instantiate our protocol for secure aggregation based on a state-of-the-art information-theoretically secure protocol SwiftAgg+. Evaluation results among 64 parties deployed on Azure virtual machines show that our protocol reduces the running time of SwiftAgg+ by 66%. The running time of parties in our protocol is reduced by at most 91% compared to that required in SwiftAgg+.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get 9b03d68b-5443-44d0-9947-11fc416bb5b7Related papers
- Hybrid Trust Multi-party Computation with Trusted Execution EnvironmentPengfei Wu, Jianting Ning, Jiamin Shen, Hongbing Wang et al.NDSS 2022
- Enabling Execution Assurance of Federated Learning at Untrusted ParticipantsXiaoli Zhang, Fengting Li, Zeyu Zhang, Qi Li et al.INFOCOM 2020 · 87 citations
- Perfectly Secure Network-Agnostic MPC Comes for FreeXiaoyu Ji, Chen-Da Liu-Zhang, Yifan SongEUROCRYPT 2026 · 1 citation
- TEEM³: Core-Independent and Cooperating Trusted Execution EnvironmentsNils Asmussen, Sebastian Haas, Carsten Weinhold, Nicholas Gordon et al.ASPLOS 2026
- Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with ErrorsTimothy Stevens, Christian Skalka, Christelle Vincent, John H. Ring et al.USENIX Security 2022
