In this paper, we study the problem of constructing private classifiers using decision trees, within the framework of differential privacy. We first construct privacy-preserving ID...
Background knowledge is an important factor in privacy preserving data publishing. Probabilistic distributionbased background knowledge is a powerful kind of background knowledge w...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu, Ke Wang, Y...
—Traditional approaches to K-anonymity provide privacy guarantees over publicly released data sets with specified quasi-identifiers. However, the most common public releases of...
We formulate and study a privacy guarantee to data owners, who share information with clients by publishing views of a proprietary database. The owner identifies the sensitive pro...
While previous works on privacy-preserving serial data publishing consider the scenario where sensitive values may persist over multiple data releases, we find that no previous wor...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu, Jia Liu, K...