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» Maintaining K-Anonymity against Incremental Updates
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SSDBM
2007
IEEE
105views Database» more  SSDBM 2007»
13 years 11 months ago
Maintaining K-Anonymity against Incremental Updates
K-anonymity is a simple yet practical mechanism to protect privacy against attacks of re-identifying individuals by joining multiple public data sources. All existing methods achi...
Jian Pei, Jian Xu, Zhibin Wang, Wei Wang 0009, Ke ...
CIKM
2008
Springer
13 years 5 months ago
Protecting location privacy against location-dependent attack in mobile services
Privacy preservation has recently received considerable attention for location-based mobile services. In this paper, we present location-dependent attack resulting from continuous...
Xiao Pan, Jianliang Xu, Xiaofeng Meng
GRC
2008
IEEE
13 years 5 months ago
Towards Real-time Performance of Data Value Hiding for Frequent Data Updates
Hiding data values in privacy-preserving data mining (PPDM) protects information against unauthorized attacks while maintaining analytical data properties. The most popular models...
Jie Wang, Justin Zhan, Jun Zhang
SIGMOD
2003
ACM
141views Database» more  SIGMOD 2003»
14 years 4 months ago
QC-Trees: An Efficient Summary Structure for Semantic OLAP
Recently, a technique called quotient cube was proposed as a summary structure for a data cube that preserves its semantics, with applications for online exploration and visualiza...
Laks V. S. Lakshmanan, Jian Pei, Yan Zhao
CVPR
2006
IEEE
13 years 10 months ago
Robust multi-target tracking using spatio-temporal context
In multi-target tracking, the maintaining of the correct identity of targets is challenging. In the presented tracking method, accurate target identification is achieved by incor...
Hieu Tat Nguyen, Qiang Ji, Arnold W. M. Smeulders