The security of organizational databases has received considerable attention in the literature in recent years. This can be attributed to a simultaneous increase in the amount of data being stored in databases, the analysis of such data, and the desire to protect confidential data. Data...

Protecting confidential, numerical data in databases from disclosure is an important issue both for commercial organizations as well as data-gathering and disseminating organizations (such as the Census Bureau). Prior studies have shown that perturbation methods are effective in protecting such...

This study discusses a new procedure for masking confidential numerical data--a procedure called data shuffling--in which the values of the confidential variables are "shuffled" among observations. The shuffled data provides a high level of data utility and minimizes the risk of disclosure. From...

Recently the New York Times reported on the University of Pittsburgh Medical Center using commercial data from Acxiom to develop analytical models to “intended to improve patients' health care outcomes and contain costs.” The article summarizes the process as follows: "The Pittsburgh health...