TIAMAT: a Tool for Interactive Analysis of Microdata Anonymization Techniques

Chenyun Dai
Gabriel Ghinita
Elisa Bertino, Purdue University
Won Won Byun

2009 VLDB conference paper


Releasing detailed data (microdata) about individuals poses a privacy threat, due to the presence of quasi-identifier (QID) attributes such as age or zip code. Several privacy paradigms have been proposed that preserve privacy by placing constraints on the value of released QIDs. However, in order to enforce these paradigms, data publishers need tools to assist them in selecting a suitable anonymization method and choosing the right system parameters. We developed TIAMAT, a tool for analysis of anonymization techniques which allows data publishers to assess the accuracy and overhead of existing anonymization techniques. The tool performs interactive, head-to-head comparison of anonymization techniques, as well as QID change-impact analysis. Other features include collection of attribute statistics, support for multiple information loss metrics and compatibility with commercial database engines.