Interactive Anonymization of Sensitive Data

There has been much recent work on algorithms for limiting disclosure in data publishing. However, these algorithms have not been put to use in any comprehensive, usable toolkit for practicioners. We will demonstrate CAT, the Cornell Anonymization Toolkit, designed for interactive anonymization. CAT has an interface that is easy to use; it guides users through the process of preparing a dataset for publication while limiting disclosure through the identification of records that have high risk under various attacker models.