The aim of this book is to give the reader a detailed introduction to the different approaches
to generating multiply imputed synthetic datasets. It describes all approaches that have been …

The paper presents an illustration and empirical study of releasing multiply imputed, fully
synthetic public use microdata. Simulations based on data from the US Current Population …

In 2006, Paul W. Holland retired from Educational Testing Service (ETS) after a career
spanning five decades. In 2008, ETS sponsored a conference, Looking Back, honoring …

Inference control in databases, also known as Statistical Disclosure Control (SDC), is about
protecting data so they can be published without revealing confidential information that can …

To limit the risks of disclosures when releasing data to the public, it has been suggested that
statistical agencies release multiply imputed, synthetic microdata. For example, the released …

In this paper, we review the role of information fusion in data privacy. To that end, we
introduce data privacy, and describe how information and data fusion are used in some …

In this paper we discuss a new theoretical basis for perturbation methods. In develo** this
new theoretical basis, we define the ideal measures of data utility and disclosure risk …

The paper proposes a new disclosure limitation procedure based on simulation. The key
feature of the proposal is to protect actual microdata by drawing artificial units from a …

Confidential business data needs protection against disclosure. Often this data is protected
by releasing sample means, variances and higher power moments. Motivated by statistical …

For continuous key variables, a measure of the individual risk of disclosure is proposed. This
risk measure, the local outlier factor, estimates the density around a unit. A selective …