In mining and integrating data from multiple sources, there are many privacy and security issues. In several different contexts, the security of the full privacy-preserving data mi...
Bart Goethals, Sven Laur, Helger Lipmaa, Taneli Mi...
Data mining, with its promise to extract valuable, previously unknown and potentially useful patterns or knowledge from large data sets that contain private information is vulnerab...
Research in secure distributed computation, which was done as part of a larger body of research in the theory of cryptography, has achieved remarkable results. It was shown that n...
Currently, many privacy-preserving data mining (PPDM) algorithms assume the semi-honest model and/or malicious model of multi-party interaction. However, both models are far from ...
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...