Cryptology ePrint Archive: Report 2017/1091

Fairness in an Unfair World: Fair Multiparty Computation from public Bulletin Boards

Arka Rai Choudhuri and Matthew Green and Abhishek Jain and Gabriel Kaptchuk and Ian Miers

Abstract: Secure multiparty computation allows mutually distrusting parties to compute a function on their private inputs such that nothing but the function output is revealed. Achieving fairness --- that all parties learn the output or no one does -- is a long studied problem with known impossibility results in the standard model if a majority of parties are dishonest.

We present a new model for achieving fairness in MPC against dishonest majority by using public bulletin boards implemented via existing infrastructure such as blockchains or Google's certificate transparency logs. We present both theoretical and practical constructions using either witness encryption or trusted hardware (such as Intel SGX).

Unlike previous works that either penalize an aborting party or achieve weaker notions such as $\Delta$-fairness, we achieve complete fairness using existing infrastructure.

Category / Keywords: cryptographic protocols / fairness

Original Publication (with minor differences): ACM CCS 2017

Date: received 9 Nov 2017, last revised 10 Nov 2017

Contact author: achoud at cs jhu edu

Available format(s): PDF | BibTeX Citation

Version: 20171110:160617 (All versions of this report)

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