In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...
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...
Abstract. Model selection is an important problem in statistics, machine learning, and data mining. In this paper, we investigate the problem of enabling multiple parties to perfor...
Reluctance of data owners to share their possibly confidential or proprietary data with others who own related databases is a serious impediment to conducting a mutually beneficia...
Ashish P. Sanil, Alan F. Karr, Xiaodong Lin, Jerom...
Research in the areas of privacy preserving techniques in databases and subsequently in privacy enhancement technologies have witnessed an explosive growth-spurt in recent years. ...