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Enforcing Input Correctness via Certification in Garbled Circuit Evaluation

  • Yihua Zhang
  • Marina Blanton
  • Fattaneh Bayatbabolghani
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10493)

Abstract

Secure multi-party computation allows a number of participants to securely evaluate a function on their private inputs and has a growing number of applications. Two standard adversarial models that treat the participants as semi-honest or malicious, respectively, are normally considered for showing security of constructions in this framework. In this work, we go beyond the standard security model in the presence of malicious participants and treat the problem of enforcing correct inputs to be entered into the computation. We achieve this by having a certification authority certify user’s information, which is consequently used in secure two-party computation based on garbled circuit evaluation. The focus of this work on enforcing correctness of garbler’s inputs via certification, as prior work already allows one to achieve this goal for circuit evaluator’s input. Thus, in this work, we put forward a novel approach for certifying user’s input and tying certification to garbler’s input used during secure function evaluation based on garbled circuits. Our construction achieves notable performance of adding only one (standard) signature verification and \(O(n\rho )\) symmetric key/hash operations to the cost of garbled circuit evaluation in the malicious model via cut-and-choose, in which \(\rho \) circuits are garbled and n is the length of the garbler’s input in bits. Security of our construction is rigorously proved in the standard model.

Keywords

Garbled circuits Input certification Input verification Secure function evaluation 

Notes

Acknowledgments

This work was supported in part by grants 1223699 and 1319090 from the National Science Foundation and FA9550-13-1-0066 from the Air Force Office of Scientific Research. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the funding agencies.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Yihua Zhang
    • 1
  • Marina Blanton
    • 2
  • Fattaneh Bayatbabolghani
    • 1
  1. 1.Computer Science and EngineeringUniversity of Notre DameNotre DameUSA
  2. 2.Computer Science and EngineeringState University of New YorkBuffaloUSA

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