Most previous research on privacy-preserving data publishing, based on the k-anonymity model, has followed the simplistic approach of homogeneously giving the same generalized val...
Wai Kit Wong, Nikos Mamoulis, David Wai-Lok Cheung
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...
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...
Economies of scale, corporate partnerships and a need to increase the efficiency of Information Technology in the Healthcare sector are leading to the construction of Regional Hea...
Tyrone Grandison, Srivatsava Ranjit Ganta, Uri Bra...
Previous works about privacy preserving serial data publishing on dynamic databases have relied on unrealistic assumptions of the nature of dynamic databases. In many applications...
Yingyi Bu, Ada Wai-Chee Fu, Raymond Chi-Wing Wong,...