Data publishing generates much concern over the protection of individual privacy. In the well-known kanonymity model and the related models such as l-diversity and (α, k)-anonymi...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu, Ke Wang, J...
-- Publishing person specific data while protecting privacy is an important problem. Existing algorithms that enforce the privacy principle called l-diversity are heuristic based d...
We identify proximity breach as a privacy threat specific to numerical sensitive attributes in anonymized data publication. Such breach occurs when an adversary concludes with hig...
Publishing microdata raises concerns of individual privacy. When there exist outlier records in the microdata, the distinguishability of the outliers enables their privacy to be e...
In some applications of privacy preserving data publishing, a practical demand is to publish a data set on multiple quasi-identifiers for multiple users simultaneously, which poses...