The ability to store vast quantities of data and the emergence of high speed networking have led to intense interest in distributed data mining. However, privacy concerns, as well ...
In this paper we explore private computation built on vector addition and its applications in privacypreserving data mining. Vector addition is a surprisingly general tool for imp...
Distributed privacy preserving data mining tools are critical for mining multiple databases with a minimum information disclosure. We present a framework including a general model...
With increasingly conceiving learning as a social activity, technological support must become more aware of the social context of the individual in order to be able to provide adeq...
Due in part to the large volume of data available today, but more importantly to privacy concerns, data are often distributed across institutional, geographical and organizational...