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SDMW
2004
Springer

Experimental Analysis of Privacy-Preserving Statistics Computation

12 years 5 months ago
Experimental Analysis of Privacy-Preserving Statistics Computation
The recent investigation of privacy-preserving data mining and other kinds of privacy-preserving distributed computation has been motivated by the growing concern about the privacy of individuals when their data is stored, aggregated, and mined for information. Building on the study of selective private function evaluation and the efforts towards practical algorithms for privacy-preserving data mining solutions, we analyze and implement solutions to an important primitive, that of computing statistics of selected data in a remote database in a privacypreserving manner. We examine solutions in different scenarios ranging from a high speed communications medium, such as a LAN or highspeed Internet connection, to a decelerated communications medium to account for worst-case communication delays such as might be provided in a wireless multihop setting. Our experimental results show that in the absence of special-purpose hardware accelerators or practical optimizations, the computational ...
Hiranmayee Subramaniam, Rebecca N. Wright, Zhiqian
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where SDMW
Authors Hiranmayee Subramaniam, Rebecca N. Wright, Zhiqiang Yang
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