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Full-Text Articles in Physical Sciences and Mathematics
Privacy-Preserving Cooperative Statistical Analysis, Wenliang Du, Mikhail J. Atallah
Privacy-Preserving Cooperative Statistical Analysis, Wenliang Du, Mikhail J. Atallah
Electrical Engineering and Computer Science - All Scholarship
The growth of the Internet opens up tremendous opportunities for cooperative computation, where the answer depends on the private inputs of separate entities. Sometimes these computations may occur between mutually untrusted entities. The problem is trivial if the context allows the conduct of these computations by a trusted entity that would know the inputs from all the participants; however if the context disallows this then the techniques of secure multi-party computation become very relevant and can provide useful solutions. Statistic analysis is a widely used computation in real life, but the known methods usually require one to know the whole …
Secure Multi-Party Computation Problems And Their Applications: A Review And Open Problems, Wenliang Du, Mikhail J. Atallah
Secure Multi-Party Computation Problems And Their Applications: A Review And Open Problems, Wenliang Du, Mikhail J. Atallah
Electrical Engineering and Computer Science - All Scholarship
The growth of the Internet has triggered tremendous opportunities for cooperative computation, where people are jointly conducting computation tasks based on the private inputs they each supplies. These computations could occur between mutually untrusted parties, or even between competitors. For example, customers might send to a remote database queries that contain private information; two competing financial organizations might jointly invest in a project that must satisfy both organizations' private and valuable constraints, and so on. Today, to conduct such computations, one entity must usually know the inputs from all the participants; however if nobody can be trusted enough to know …