FairplayMP: a system for secure multi-party computation. We present FairplayMP (for ”Fairplay Multi-Party”), a system for secure multi-party computation. Secure computation is one of the great achievements of modern cryptography, enabling a set of untrusting parties to compute any function of their private inputs while revealing nothing but the result of the function. In a sense, FairplayMP lets the parties run a joint computation that emulates a trusted party which receives the inputs from the parties, computes the function, and privately informs the parties of their outputs. FairplayMP operates by receiving a high-level language description of a function and a configuration file describing the participating parties. The system compiles the function into a description as a Boolean circuit, and perform a distributed evaluation of the circuit while revealing nothing else. FairplayMP supplements the Fairplay system [16], which supported secure computation between two parties. The underlying protocol of FairplayMP is the Beaver-Micali-Rogaway (BMR) protocol which runs in a constant number of communication rounds (eight rounds in our implementation). We modified the BMR protocol in a novel way and considerably improved its performance by using the Ben-Or-Goldwasser-Wigderson (BGW) protocol for the purpose of constructing gate tables. We chose to use this protocol since we believe that the number of communication rounds is a major factor on the overall performance of the protocol. We conducted different experiments which measure the effect of different parameters on the performance of the system and demonstrate its scalability. (We can now tell, for example, that running a second-price auction between four bidders, using five computation players, takes about 8 seconds.)

This software is also peer reviewed by journal TOMS.

References in zbMATH (referenced in 13 articles )

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  1. Burra, Sai Sheshank; Larraia, Enrique; Nielsen, Jesper Buus; Nordholt, Peter Sebastian; Orlandi, Claudio; Orsini, Emmanuela; Scholl, Peter; Smart, Nigel P.: High-performance multi-party computation for binary circuits based on oblivious transfer (2021)
  2. Steverink, Lisa; Veugen, Thijs; van Gijzen, Martin B.: Approximating eigenvectors with fixed-point arithmetic: a step towards secure spectral clustering (2021)
  3. Alhassan, Masaud Y.; Günther, Daniel; Kiss, Ágnes; Schneider, Thomas: Efficient and scalable universal circuits (2020)
  4. Asharov, Gilad; Lindell, Yehuda; Schneider, Thomas; Zohner, Michael: More efficient oblivious transfer extensions (2017)
  5. Lindell, Yehuda; Pinkas, Benny; Smart, Nigel P.; Yanai, Avishay: Efficient constant round multi-party computation combining BMR and SPDZ (2015)
  6. Bonchi, Francesco; Gionis, Aristides; Tassa, Tamir: Identity obfuscation in graphs through the information theoretic lens (2014) ioport
  7. Goodrich, Michael T.: Spin-the-bottle sort and annealing sort: oblivious sorting via round-robin random comparisons (2014)
  8. Kamara, Seny; Mohassel, Payman; Raykova, Mariana; Sadeghian, Saeed: Scaling private set intersection to billion-element sets (2014) ioport
  9. Wallrabenstein, John Ross; Clifton, Chris: Privacy preserving Tâtonnement (2014) ioport
  10. Micciancio, Daniele; Tessaro, Stefano: An equational approach to secure multi-party computation (2013)
  11. Choi, Seung Geol; Hwang, Kyung-Wook; Katz, Jonathan; Malkin, Tal; Rubenstein, Dan: Secure multi-party computation of Boolean circuits with applications to privacy in on-line marketplaces (2012)
  12. Kerschbaum, Florian: Sicheres und nachhaltiges benchmarking in der cloud - eine mehrparteien-cloud-anwendung ohne vertrauenswürdigen dienstanbieter (2011) ioport
  13. Eurich, Markus; Oertel, Nina; Boutellier, Roman: The impact of perceived privacy risks on organizations’ willingness to share item-level event data across the supply chain (2010) ioport