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dc.contributor.authorVolgushev, Nikolaj
dc.contributor.authorLapets, Andrei
dc.contributor.authorBestavros, Azer
dc.date.accessioned2017-04-26T18:43:33Z
dc.date.available2017-04-26T18:43:33Z
dc.date.issued2015-08-29
dc.identifier.citationVolgushev, Nikolaj; Lapets, Andrei; Bestavros, Azer. Scather: Programming with Multi-party Computation and MapReduce. Technical Report BU-CS-TR 2015-010, Computer Science Department, Boston University, August 29, 2015.
dc.identifier.urihttps://hdl.handle.net/2144/21774
dc.description.abstractWe present a prototype of a distributed computational infrastructure, an associated high level programming language, and an underlying formal framework that allow multiple parties to leverage their own cloud-based computational resources (capable of supporting MapReduce [27] operations) in concert with multi-party computation (MPC) to execute statistical analysis algorithms that have privacy-preserving properties. Our architecture allows a data analyst unfamiliar with MPC to: (1) author an analysis algorithm that is agnostic with regard to data privacy policies, (2) to use an automated process to derive algorithm implementation variants that have different privacy and performance properties, and (3) to compile those implementation variants so that they can be deployed on an infrastructures that allows computations to take place locally within each participant’s MapReduce cluster as well as across all the participants’ clusters using an MPC protocol. We describe implementation details of the architecture, discuss and demonstrate how the formal framework enables the exploration of tradeoffs between the efficiency and privacy properties of an analysis algorithm, and present two example applications that illustrate how such an infrastructure can be utilized in practice.
dc.description.sponsorshipThis work was supported in part by NSF Grants: #1430145, #1414119, #1347522, and #1012798.
dc.language.isoen_US
dc.publisherComputer Science Department, Boston University
dc.relation.ispartofseriesBUCS Technical Reports;BUCS-TR-2015-010
dc.subjectCloud computing
dc.subjectMulti-party computation (MPC)
dc.titleScather: programming with multi-party computation and MapReduce
dc.typeTechnical Report


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