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Secure Multi-Party Computation

Dong, Renren

Abstract Details

2009, Master of Science (MS), Bowling Green State University, Computer Science.
Data mining algorithms help reveal hidden information in a repository. Distributed mining 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.
Ray Kresman, PhD (Advisor)
So-Hsiang Chou, PhD (Committee Member)
Mohammad Dadfar, PhD (Committee Member)
73 p.

Recommended Citations

Citations

  • Dong, R. (2009). Secure Multi-Party Computation [Master's thesis, Bowling Green State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1241807339

    APA Style (7th edition)

  • Dong, Renren. Secure Multi-Party Computation. 2009. Bowling Green State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1241807339.

    MLA Style (8th edition)

  • Dong, Renren. "Secure Multi-Party Computation." Master's thesis, Bowling Green State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1241807339

    Chicago Manual of Style (17th edition)