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...
People-centric urban sensing is a new paradigm gaining popularity. A main obstacle to its widespread deployment and adoption are the privacy concerns of participating individuals. ...
The proliferation of sensors in devices of frequent use, such as mobile phones, offers unprecedented opportunities for forming selfselected communities around shared sensory data ...
Nam Pham, Raghu K. Ganti, Yusuf S. Uddin, Suman Na...
Currently, many privacy-preserving data mining (PPDM) algorithms assume the semi-honest model and/or malicious model of multi-party interaction. However, both models are far from ...
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