Data mining is frequently obstructed by privacy concerns. In many cases data is distributed, and bringing the data together in one place for analysis is not possible due to privac...
To preserve client privacy in the data mining process, a variety of techniques based on random perturbation of individual data records have been proposed recently. In this paper, ...
Privacy concerns have become an important issue in data mining. A popular way to preserve privacy is to randomize the dataset to be mined in a systematic way and mine the randomiz...
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...
Motivated by the insufficiency of the existing quasi-identifier/sensitiveattribute (QI-SA) framework on modeling real-world privacy requirements for data publishing, we propose ...
Xin Jin, Mingyang Zhang, Nan Zhang 0004, Gautam Da...