Distance-based record linkage (DBRL) is a common approach to empirically assessing the disclosure risk in SDC-protected microdata. Usually, the Euclidean distance is used. In this paper, we explore the potential advantages of using the Mahalanobis distance for DBRL. We illustrate our point for partially synthetic microdata and show that, in some cases, Mahalanobis DBRL can yield a very high re-...

This paper discusses the development of a model of the household migration behavior of a nation’s population. From information synthesized from across available microdata sources which are each temporally, spatially, or topically inconsistent in coverage, we learned decision trees and instantiated agents in an agent-based model. The generative results of the whole-country simulation of this ABM...

Individual data records are essential for empirical research, and yet due to the very precious information they contain, their release poses a problem to the confidentiality of the individuals concerned. In this paper we give a high level description of a privacy-preserving microdata sharing system wherein subjects identifiers are replaced by cryptographic pseudonyms. The resulting system facil...

The TokuFS file system outperforms write-optimized file systems by an order of magnitude on microdata write workloads, and outperforms read-optimized file systems by an order of magnitude on read workloads. Microdata write workloads include creating and destroying many small files, performing small unaligned writes within large files, and updating metadata. TokuFS is implemented using Fractal T...

Scientists increasingly express the desire to use official statistics microdata for their own empirical economic and social research. In Germany, the road prescribed by the legislator is that microdata should be converted into a so called “factually” anonymised form, before they are made available to scientists. Accordingly, data items are regarded as sufficiently anonymised, if the expenditure...

Government statistical agencies often apply statistical disclosure limitation techniques to survey microdata to protect the confidentiality of respondents. There is a need for valid and practical ways to assess the protection provided. This paper develops some simple methods for disclosure limitation techniques which perturb the values of categorical identifying variables. The methods are appli...

Privacy issues during data publishing is an increasing concern of involved entities. The problem is addressed in the field of statistical disclosure control with the aim of producing protected datasets that are also useful for interested end users such as government agencies and research communities. The problem of producing useful protected datasets is addressed in multiple computational priva...

1. National Statistical Institutes are able to release microdata sets only on the condition that the privacy of respondents is safe and that the event of breach of confidentiality is extremely unlikely. Different institutions adopt different definitions of disclosure, of disclosure risk and use different models to estimate such risk and protect microdata set. In all cases, the aim is the same: ...

We propose a strategy for disclosure risk evaluation and disclosure control of a microdata set based on fitting decomposable models of a multiway contingency table corresponding to the microdata set. By fitting decomposable models, we can evaluate per-record identification (or re-identification) risk of a microdata set. Furthermore we can easily determine swappability of risky records which doe...

Schema.org offers to web developers the opportunity to enrich a website’s content with microdata and schema.org. For large websites, implementing microdata can take a lot of time. In general, it is necessary to perform two main activities, for which we lack methods and tools. The first consists in designing what we call the website schema.org, which is the fragment of schema.org that is relevan...