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Studies from Soochow University Reveal New Findings on Information Technology (A communication-efficient private matching scheme in Client-Server...

July 8, 2014



Studies from Soochow University Reveal New Findings on Information Technology (A communication-efficient private matching scheme in Client-Server model)

By a News Reporter-Staff News Editor at Information Technology Newsweekly -- Research findings on Information Technology are discussed in a new report. According to news reporting originating from Taipei, Taiwan, by VerticalNews correspondents, research stated, "In a Private Matching (PM) scheme, the client C has a dataset X of m elements, and the server S has a dataset Y of n elements. The client C can learn the set intersection X boolean AND Y without leaking any information to the server S. Previously, the most efficient PM scheme requires communication of complexity (O) over tilde (m + n), which increases linearly with n. This may not be efficient enough in Client-Server models because the server's dataset Y is usually large."

Our news editors obtained a quote from the research from Soochow University, "In this paper, we propose a PM scheme based on Oblivious Transfer (OT) and universal hash function. Our scheme requires communication of complexity (O) over tilde (m. log(2)n). Thus, our scheme is especially suitable for Client-Server models. We show that our scheme becomes more efficient when log(2)(mn)(1+Delta) = (O) over tilde (n/m) for security parameter Delta > 0. However, utilizing the universal hash function would cause a mismatch issue which affects the accuracy of the PM scheme. In addition, it leaks the server's information."

According to the news editors, the research concluded: "Therefore, we define approximate PM by relaxing the definition of PM; it is proved to be almost as secure as a PM scheme in a Client-Server model with proper configurations."

For more information on this research see: A communication-efficient private matching scheme in Client-Server model. Information Sciences, 2014;275():348-359. Information Sciences can be contacted at: Elsevier Science Inc, 360 Park Ave South, New York, NY 10010-1710, USA. (Elsevier - www.elsevier.com; Information Sciences - www.elsevier.com/wps/product/cws_home/505730)

The news editors report that additional information may be obtained by contacting M.E. Wu, Soochow Univ, Dept. of Math, Taipei, Taiwan. Additional authors for this research include S.Y. Chang, C.J. Lu and H.M. Sun.

Keywords for this news article include: Asia, Taipei, Taiwan, Information Technology

Our reports deliver fact-based news of research and discoveries from around the world. Copyright 2014, NewsRx LLC


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Source: Information Technology Newsweekly


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