Secure Multi-Party Computation
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2009
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ndltd-OhioLink-oai-etd.ohiolink.edu-bgsu12418073392021-08-03T05:28:55Z Secure Multi-Party Computation Dong, Renren AIDA-A EDHC algorithms Hamiltonian cycles edge-disjoint HC Graph Data mining algorithms help reveal hidden information in a repository. Distributedmining algorithms meet this need by distributing data and computation. One of the mostimportant issues of these algorithms is how to safely mine the data. Secure Multiparty Computation (SMC), a framework for safe mining of distributed data, provides some security promises of the computation.This thesis addresses certain aspects of SMC including the role of Hamiltonian and edge-disjoint Hamiltonian cycles. We formalize the notion of trust in a network and show thatcertain network configurations are better than others. We propose and analyze an algorithm for id assignment in networks that outperforms an existing algorithm. 2009-08-12 English text Bowling Green State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1241807339 http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1241807339 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |
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English |
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topic |
AIDA-A EDHC algorithms Hamiltonian cycles edge-disjoint HC Graph |
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AIDA-A EDHC algorithms Hamiltonian cycles edge-disjoint HC Graph Dong, Renren Secure Multi-Party Computation |
author |
Dong, Renren |
author_facet |
Dong, Renren |
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Dong, Renren |
title |
Secure Multi-Party Computation |
title_short |
Secure Multi-Party Computation |
title_full |
Secure Multi-Party Computation |
title_fullStr |
Secure Multi-Party Computation |
title_full_unstemmed |
Secure Multi-Party Computation |
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secure multi-party computation |
publisher |
Bowling Green State University / OhioLINK |
publishDate |
2009 |
url |
http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1241807339 |
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AT dongrenren securemultipartycomputation |
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1719420689157455872 |