Abstract. Privacy protection in publishing transaction data is an important problem. A key feature of transaction data is the extreme sparsity, which renders any single technique i...
Re-identification is a major privacy threat to public datasets containing individual records. Many privacy protection algorithms rely on generalization and suppression of "qu...
We study the problem of anonymizing data with quasi-sensitive attributes. Quasi-sensitive attributes are not sensitive by themselves, but certain values or their combinations may ...
Data anonymization techniques have been the subject of intense investigation in recent years, for many kinds of structured data, including tabular, item set and graph data. They e...
A popular model for protecting privacy when person-specific data is released is k-anonymity. A dataset is k-anonymous if each record is identical to at least (k - 1) other records ...