Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Incognito: efficient full-domain K-anonymity
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
L-diversity: Privacy beyond k-anonymity
ACM Transactions on Knowledge Discovery from Data (TKDD)
Privacy: Theory meets Practice on the Map
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
"Un-googling" publications: the ethics and problems of anonymization
CHI '13 Extended Abstracts on Human Factors in Computing Systems
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There has been much recent work on algorithms for limiting disclosure in data publishing, however they have not been put to use in any 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.