: Achieving privacy preservation in a data-sharing computing environment is becoming a challenging problem. Some organisations may have published privacy policies, which promise pr...
Privacy-preserving data mining (PPDM) is an important topic to both industry and academia. In general there are two approaches to tackling PPDM, one is statistics-based and the oth...
Patrick Sharkey, Hongwei Tian, Weining Zhang, Shou...
Random perturbation is a promising technique for privacy preserving data mining. It retains an original sensitive value with a certain probability and replaces it with a random va...
—We demonstrate DPCube, a component in our Health Information DE-identification (HIDE) framework, for releasing differentially private data cubes (or multi-dimensional histogram...
The k-anonymity privacy requirement for publishing microdata requires that each equivalence class (i.e., a set of records that are indistinguishable from each other with respect to...