{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/122871"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/122871","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Distributed correlation generators","abstract":"We study the problem of distributed correlation generators wherein n parties wish to simulate unbounded samples from a joint distribution D = Di x D2 X ... x D[subscript n], once they are initialized using randomness sampled from a (possibly different) correlated distribution. We wish to ensure that these samples are computationally indistinguishable from i.i.d. samples from D. Furthermore, we wish to ensure security even against an adversary who corrupts a subset of the parties and obtains their internal (initialization) state. Our contributions are three-fold. First, we define the notion of distributed (noninteractive) correlation generators and show its connection to other cryptographic primitives. Secondly, assuming the existence of indistinguishability obfuscators, we show a construction of distributed correlation generators for a large and natural class of joint distributions that we call conditionally sampleable distributions. Finally, we show a construction for the subclass of additive-spooky distributions assuming private constrained pseudorandom functions (private CPRFs).","abstract_html":"We study the problem of distributed correlation generators wherein n parties wish to simulate unbounded samples from a joint distribution D = Di x D2 X ... x D[subscript n], once they are initialized using randomness sampled from a (possibly different) correlated distribution. We wish to ensure that these samples are computationally indistinguishable from i.i.d. samples from D. Furthermore, we wish to ensure security even against an adversary who corrupts a subset of the parties and obtains their internal (initialization) state. Our contributions are three-fold. First, we define the notion of distributed (noninteractive) correlation generators and show its connection to other cryptographic primitives. Secondly, assuming the existence of indistinguishability obfuscators, we show a construction of distributed correlation generators for a large and natural class of joint distributions that we call conditionally sampleable distributions. Finally, we show a construction for the subclass of additive-spooky distributions assuming private constrained pseudorandom functions (private CPRFs).","abstract_has_math":false,"creators":["Hui, Joseph,S.M.Massachusetts Institute of Technology."],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","school":null,"contributors":[],"advisors":["Vinod Vaikuntanathan."],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018","date_published":"2018","updated_at":"2026-07-22T22:21:20Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["MIT theses are protected by copyright. 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We wish to ensure that these samples are computationally indistinguishable from i.i.d. samples from D. Furthermore, we wish to ensure security even against an adversary who corrupts a subset of the parties and obtains their internal (initialization) state. Our contributions are three-fold. First, we define the notion of distributed (noninteractive) correlation generators and show its connection to other cryptographic primitives. Secondly, assuming the existence of indistinguishability obfuscators, we show a construction of distributed correlation generators for a large and natural class of joint distributions that we call conditionally sampleable distributions. Finally, we show a construction for the subclass of additive-spooky distributions assuming private constrained pseudorandom functions (private CPRFs)."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Distributed correlation generators"]}]}],"canonical_facts":{"dc:contributor.advisor":["Vinod Vaikuntanathan."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","EECS"],"dc:contributor.other":["Massachusetts Institute of Technology. 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Furthermore, we wish to ensure security even against an adversary who corrupts a subset of the parties and obtains their internal (initialization) state. Our contributions are three-fold. First, we define the notion of distributed (noninteractive) correlation generators and show its connection to other cryptographic primitives. Secondly, assuming the existence of indistinguishability obfuscators, we show a construction of distributed correlation generators for a large and natural class of joint distributions that we call conditionally sampleable distributions. Finally, we show a construction for the subclass of additive-spooky distributions assuming private constrained pseudorandom functions (private CPRFs)."],"dc:description.degree":["S.M."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/122871"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["MIT theses are protected by copyright. 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