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
It is often highly valuable for organizations to have their data analyzed by external agents. However, any program that computes on potentially sensitive data risks leaking inform...
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...
Combining and analyzing data collected at multiple locations is critical for a wide variety of applications, such as detecting and diagnosing malicious attacks or computing an acc...
Benny Applebaum, Haakon Ringberg, Michael J. Freed...
Recommender systems enable merchants to assist customers in finding products that best satisfy their needs. Unfortunately, current recommender systems suffer from various privacy...