We present an efficient protocol for the privacy-preserving, distributed learning of decision-tree classifiers. Our protocol allows a user to construct a classifier on a database h...
This paper presents a hierarchy of privacy notions that covers multiple anonymity and unlinkability variants. The underlying definitions, which are based on the idea of indistingu...
In this note, we report on the first large-scale and practical application of secure multiparty computation, which took place in January 2008. We also report on the novel cryptogr...
Peter Bogetoft, Dan Lund Christensen, Ivan Damg&ar...