Data mining tasks such as supervised classification can often benefit from a large training dataset. However, in many application domains, privacy concerns can hinder the construc...
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 ...
Randomized Response techniques have been empirically investigated in privacy preserving association rule mining. However, previous research on privacy preserving market basket data...
Motivated by the insufficiency of the existing quasi-identifier/sensitiveattribute (QI-SA) framework on modeling real-world privacy requirements for data publishing, we propose ...
Xin Jin, Mingyang Zhang, Nan Zhang 0004, Gautam Da...
We consider privacy preserving decision tree induction via ID3 in the case where the training data is horizontally or vertically distributed. Furthermore, we consider the same pro...