Distributed correlation generators
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2019
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| Online Access: | https://hdl.handle.net/1721.1/122871 |
| _version_ | 1826198240763052032 |
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| author | Hui, Joseph,S.M.Massachusetts Institute of Technology. |
| author2 | Vinod Vaikuntanathan. |
| author_facet | Vinod Vaikuntanathan. Hui, Joseph,S.M.Massachusetts Institute of Technology. |
| author_sort | Hui, Joseph,S.M.Massachusetts Institute of Technology. |
| collection | MIT |
| description | Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018 |
| first_indexed | 2024-09-23T11:01:36Z |
| format | Thesis |
| id | mit-1721.1/122871 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T11:01:36Z |
| publishDate | 2019 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1228712019-11-21T03:12:11Z Distributed correlation generators Hui, Joseph,S.M.Massachusetts Institute of Technology. Vinod Vaikuntanathan. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Electrical Engineering and Computer Science. Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018 Cataloged from PDF version of thesis. Includes bibliographical references (pages 39-40). 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). by Joseph Hui. S.M. S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science 2019-11-12T17:40:34Z 2019-11-12T17:40:34Z 2018 2018 Thesis https://hdl.handle.net/1721.1/122871 1126650513 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 40 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Hui, Joseph,S.M.Massachusetts Institute of Technology. Distributed correlation generators |
| title | Distributed correlation generators |
| title_full | Distributed correlation generators |
| title_fullStr | Distributed correlation generators |
| title_full_unstemmed | Distributed correlation generators |
| title_short | Distributed correlation generators |
| title_sort | distributed correlation generators |
| topic | Electrical Engineering and Computer Science. |
| url | https://hdl.handle.net/1721.1/122871 |
| work_keys_str_mv | AT huijosephsmmassachusettsinstituteoftechnology distributedcorrelationgenerators |