Abstract. As a novel research direction, privacy-preserving data mining (PPDM) has received a great deal of attentions from more and more researchers, and a large number of PPDM al...
Secure multiparty computation allows parties to jointly compute a function of their private inputs without revealing anything but the output. Theoretical results [2] provide a gen...
Abstract--This paper presents a framework for privacypreserving Gaussian Mixture Model computations. Specifically, we consider a scenario where a central service wants to learn the...
In order to safeguard a sensitive database, we must ensure both its privacy and its longevity. However, privacy and longevity tend to be competing objectives. We show how to desig...
Bob Mungamuru, Hector Garcia-Molina, Subhasish Mit...
Abstract. Privacy issues are a major burden for the acceptance of pervasive applications. They may ultimately result in the rejection of new services despite their functional beneï...