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dc.contributor.advisorHerbordt, Martin C.en_US
dc.contributor.advisorVaria, Mayanken_US
dc.contributor.authorWolfe, Pierre-Francois W.en_US
dc.date.accessioned2021-05-26T19:03:23Z
dc.date.available2021-05-26T19:03:23Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/2144/42608
dc.description.abstractBig data utilizes large amounts of processing resources requiring either greater efficiency or more selectivity. The collection and managing of such large pools of data also introduces more opportunities for compromised security and privacy, necessitating more attentive planning and mitigations. Multi-Party Computation (MPC) is a technique enabling confidential data from multiple sources to be processed securely, only revealing agreed-upon results. Currently, adoption is limited by the challenge of basing a complete system on available software libraries. Many libraries require expertise in cryptography, do not efficiently address the computation overhead of employing MPC, and leave deployment considerations to the user. In this work we consider the available MPC protocols, changes in computer hardware, and growth of cloud computing. We propose a cloud-deployed MPC as a Service (MPCaaS) to help eliminate the barriers to adoption and enable more organizations and individuals to handle their shared data processing securely. The growing presence of Field Programmable Gate Array (FPGA) hardware in datacenters enables accelerated computing as well as low latency, high bandwidth communication that bolsters the performance of MPC. Developing an abstract service that employs this hardware will democratize access to MPC, rather than restricting it to the small overlapping pools of users knowledgeable about both cryptography and hardware accelerators. A hardware proof of concept we have implemented at BU supports this idea. We deployed an efficient three-party Secret Sharing (SS) protocol supporting both Boolean and arithmetic shares on FPGA hardware. We compare our hardware design to the original authors' software implementations of Secret Sharing and to research results accelerating MPC protocols based on Garbled Circuits with FPGAs. Our conclusion is that Secret Sharing in the datacenter is competitive and, when implemented on FPGA hardware, is able to use at least 10$\times$ fewer computer resources than the original work using CPUs. Finally, we describe the ongoing work and envision research stages that will help us to build a complete MPCaaS system.en_US
dc.language.isoen_US
dc.rightsAttribution 4.0 Internationalen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectComputer engineeringen_US
dc.titleEnabling secure multi-party computation with FPGAs in the datacenteren_US
dc.typeThesis/Dissertationen_US
dc.date.updated2021-05-15T07:03:45Z
etd.degree.nameMaster of Scienceen_US
etd.degree.levelmastersen_US
etd.degree.disciplineElectrical & Computer Engineeringen_US
etd.degree.grantorBoston Universityen_US
dc.identifier.orcid0000-0002-6672-2618


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International