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» Privacy: preserving trajectory collection
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PAISI
2010
Springer
13 years 5 months ago
Efficient Privacy Preserving K-Means Clustering
Abstract. This paper introduces an efficient privacy-preserving protocol for distributed K-means clustering over an arbitrary partitioned data, shared among N parties. Clustering i...
Maneesh Upmanyu, Anoop M. Namboodiri, Kannan Srina...
PET
2010
Springer
13 years 11 months ago
Collaborative, Privacy-Preserving Data Aggregation at Scale
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...
IEEESP
2010
101views more  IEEESP 2010»
13 years 6 months ago
Preserving Privacy Based on Semantic Policy Tools
Abstract—Private data of individuals is constantly being collected, analyzed, and stored by different kinds of organizations: shopping sites to provide better service and recomme...
Lalana Kagal, Joe Pato
DKE
2010
167views more  DKE 2010»
13 years 4 months ago
Discovering private trajectories using background information
Trajectories are spatio-temporal traces of moving objects which contain valuable information to be harvested by spatio-temporal data mining techniques. Applications like city traf...
Emre Kaplan, Thomas Brochmann Pedersen, Erkay Sava...
CHI
2006
ACM
14 years 8 months ago
Putting people in their place: an anonymous and privacy-sensitive approach to collecting sensed data in location-based applicati
The emergence of location-based computing promises new and compelling applications, but raises very real privacy risks. Existing approaches to privacy generally treat people as th...
Karen P. Tang, Pedram Keyani, James Fogarty, Jason...