Distribution-based Microdata Anonymization

On the Identification of Property Based Generalizations in Microdata Anonymization

Majority of the search algorithms in microdata anonymization restrict themselves to a single privacy property and a single criteria to optimize. The solutions obtained are therefore of limited application since adherence to multiple privacy models is required to impede different forms of privacy attacks. Towards this end, we propose the concept of a property based generalization (PBG) to captur...

An Algorithm for k-Anonymity-Based Fingerprinting

The anonymization of sensitive microdata (e.g. medical health records) is a widely-studied topic in the research community. A still unsolved problem is the limited informative value of anonymized microdata that often rules out further processing (e.g. statistical analysis). Thus, a tradeoff between anonymity and data precision has to be made, resulting in the release of partially anonymized mic...

Anonymity: A Formalization of Privacy - `-Diversity

Anonymization of published microdata has become a very important topic nowadays. The major difficulty is to publish data of individuals in a manner that the released table both provides enough information to the public and prevents disclosure of sensitive information. Therefore, several authors proposed definitions of privacy to get anonymous microdata. One definition is called k-Anonymity and ...

Anonymity: Formalisation of Privacy – k-anonymity

Microdata is the basis of statistical studies. If microdata is released, it can leak sensitive information about the participants, even if identifiers like name or social security number are removed. A proper anonymization for statistical microdata is essential. K-anonymity has been intensively discussed as a measure for anonymity in statistical data. Quasi identifiers are attributes that might...

Desemantization for Numerical Microdata Anonymization