Sciweavers

359 search results - page 9 / 72
» A Clustering Approach for Achieving Data Privacy
Sort
View
KDD
2010
ACM
279views Data Mining» more  KDD 2010»
13 years 11 months ago
Unifying dependent clustering and disparate clustering for non-homogeneous data
Modern data mining settings involve a combination of attributevalued descriptors over entities as well as specified relationships between these entities. We present an approach t...
M. Shahriar Hossain, Satish Tadepalli, Layne T. Wa...
DASFAA
2007
IEEE
178views Database» more  DASFAA 2007»
14 years 1 months ago
ClusterSheddy : Load Shedding Using Moving Clusters over Spatio-temporal Data Streams
Abstract. Moving object environments are characterized by large numbers of objects continuously sending location updates. At times, data arrival rates may spike up, causing the loa...
Rimma V. Nehme, Elke A. Rundensteiner
COSIT
2005
Springer
95views GIS» more  COSIT 2005»
14 years 27 days ago
Simulation of Obfuscation and Negotiation for Location Privacy
Abstract. Current mobile computing systems can automatically sense and communicate detailed data about a person’s location. Location privacy is an urgent research issue because c...
Matt Duckham, Lars Kulik
CRYPTO
2012
Springer
241views Cryptology» more  CRYPTO 2012»
11 years 9 months ago
Crowd-Blending Privacy
We introduce a new definition of privacy called crowd-blending privacy that strictly relaxes the notion of differential privacy. Roughly speaking, k-crowd blending private saniti...
Johannes Gehrke, Michael Hay, Edward Lui, Rafael P...
ICDM
2009
IEEE
130views Data Mining» more  ICDM 2009»
13 years 5 months ago
Efficient Anonymizations with Enhanced Utility
The k-anonymization method is a commonly used privacy-preserving technique. Previous studies used various measures of utility that aim at enhancing the correlation between the orig...
Jacob Goldberger, Tamir Tassa