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dc.rights.licenseRestricted to current Rensselaer faculty, staff and students. Access inquiries may be directed to the Rensselaer Libraries.
dc.contributorZikas, Vassilis
dc.contributorMagdon-Ismail, Malik
dc.contributorMilanova, Ana
dc.contributor.authorHadley, Connor
dc.date.accessioned2021-11-03T09:01:59Z
dc.date.available2021-11-03T09:01:59Z
dc.date.created2018-07-27T15:39:19Z
dc.date.issued2018-05
dc.identifier.urihttps://hdl.handle.net/20.500.13015/2239
dc.descriptionMay 2018
dc.descriptionSchool of Science
dc.description.abstractThis paper examines the problem of learning information on multiple private databases in a quick and secure manner. The owners of such databases may either not desire to or are otherwise unable to leak information about their respective databases, despite the desired information possibly being entirely benign in nature. For example, to reference an earlier paper creating the DJoin system, one may wish to study the correlation between disease and travel to certain regions of the world, but not have access to the information required for this process. This project builds upon past attempts at providing a system to answer this problem, with a focus on improving the scalability as the number of datasets being examined increases.
dc.description.abstractAs such, this paper introduces the Secure Multiparty Differentially Private Mechanism, or MDP, designed to improve upon past works in this field, and offer a universal solution to the problem that works regardless of the number of parties involved.
dc.language.isoENG
dc.publisherRensselaer Polytechnic Institute, Troy, NY
dc.relation.ispartofRensselaer Theses and Dissertations Online Collection
dc.subjectComputer science
dc.titleDifferentially private set intersection cardinalities in the multiparty setting
dc.typeElectronic thesis
dc.typeThesis
dc.digitool.pid179122
dc.digitool.pid179123
dc.digitool.pid179124
dc.rights.holderThis electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
dc.description.degreeMS
dc.relation.departmentDept. of Computer Science


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