Paper 2023/1744

Don't Eject the Impostor: Fast Three-Party Computation With a Known Cheater (Full Version)

Andreas Brüggemann, Technical University of Darmstadt, Germany
Oliver Schick, Technical University of Darmstadt, Germany
Thomas Schneider, Technical University of Darmstadt, Germany
Ajith Suresh, Technology Innovation Institute, Abu Dhabi
Hossein Yalame, Technical University of Darmstadt, Germany

Secure multi-party computation (MPC) enables (joint) computations on sensitive data while maintaining privacy. In real-world scenarios, asymmetric trust assumptions are often most realistic, where one somewhat trustworthy entity interacts with smaller clients. We generalize previous two-party computation (2PC) protocols like MUSE (USENIX Security'21) and SIMC (USENIX Security'22) to the three-party setting (3PC) with one malicious party, avoiding the performance limitations of dishonest-majority inherent to 2PC. We introduce two protocols, Auxiliator and Socium, in a machine learning (ML) friendly design with a fast online phase and novel verification techniques in the setup phase. These protocols bridge the gap between prior 3PC approaches that considered either fully semi-honest or malicious settings. Auxiliator enhances the semi-honest two-party setting with a malicious helper, significantly improving communication by at least two orders of magnitude. Socium extends the client-malicious setting with one malicious client and a semi-honest server, achieving substantial communication improvement by at least one order of magnitude compared to SIMC. Besides an implementation of our new protocols, we provide the first open-source implementation of the semi-honest 3PC protocol ASTRA (CCSW'19) and a variant of the malicious 3PC protocol SWIFT (USENIX Security'21).

Note: This is the full version of our research paper that has been accepted for publication at the 2024 IEEE Security & Privacy (IEEE S&P) conference.

Available format(s)
Cryptographic protocols
Publication info
Published elsewhere. Major revision. IEEE Security & Privacy (IEEE S&P) 2024
multi-party computationMPC3PCclient-malicious settingasymmetric trustprivacy-preserving machine learningPPML
Contact author(s)
brueggemann @ encrypto cs tu-darmstadt de
oliver schick @ protonmail com
schneider @ encrypto cs tu-darmstadt de
ajith suresh @ tii ae
yalame @ encrypto cs tu-darmstadt de
2023-11-13: approved
2023-11-11: received
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      author = {Andreas Brüggemann and Oliver Schick and Thomas Schneider and Ajith Suresh and Hossein Yalame},
      title = {Don't Eject the Impostor: Fast Three-Party Computation With a Known Cheater (Full Version)},
      howpublished = {Cryptology ePrint Archive, Paper 2023/1744},
      year = {2023},
      note = {\url{}},
      url = {}
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