In this paper, we study the classification problem involving information spanning multiple private databases. The privacy challenges lie in the facts that data cannot be collected...
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...
We introduce a new, generic framework for private data analysis. The goal of private data analysis is to release aggregate information about a data set while protecting the privac...
We address privacy-preserving classification problem in a distributed system. Randomization has been the approach proposed to preserve privacy in such scenario. However, this appr...
We present parallel algorithms for building decision-tree classifiers on shared-memory multiprocessor (SMP) systems. The proposed algorithms span the gamut of data and task parall...
Mohammed Javeed Zaki, Ching-Tien Ho, Rakesh Agrawa...