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» Anonymity for continuous data publishing
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TMC
2008
159views more  TMC 2008»
14 years 11 months ago
Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms
Continued advances in mobile networks and positioning technologies have created a strong market push for location-based applications. Examples include location-aware emergency resp...
Bugra Gedik, Ling Liu
104
Voted
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
16 years 25 days ago
Privacy-Preserving Data Mining through Knowledge Model Sharing
Privacy-preserving data mining (PPDM) is an important topic to both industry and academia. In general there are two approaches to tackling PPDM, one is statistics-based and the oth...
Patrick Sharkey, Hongwei Tian, Weining Zhang, Shou...
85
Voted
COLCOM
2007
IEEE
15 years 6 months ago
Privacy protection on sliding window of data streams
—In many applications, transaction data arrive in the form of high speed data streams. These data contain a lot of information about customers that needs to be carefully managed ...
Weiping Wang 0001, Jianzhong Li, Chunyu Ai, Yingsh...
91
Voted
SIGMOD
2010
ACM
274views Database» more  SIGMOD 2010»
15 years 5 months ago
K-isomorphism: privacy preserving network publication against structural attacks
Serious concerns on privacy protection in social networks have been raised in recent years; however, research in this area is still in its infancy. The problem is challenging due ...
James Cheng, Ada Wai-Chee Fu, Jia Liu
239
Voted
ICDE
2009
IEEE
392views Database» more  ICDE 2009»
17 years 4 days ago
FF-Anonymity: When Quasi-Identifiers Are Missing
Existing approaches on privacy-preserving data publishing rely on the assumption that data can be divided into quasi-identifier attributes (QI) and sensitive attribute (SA). This ...
Ada Wai-Chee Fu, Ke Wang, Raymond Chi-Wing Wong, Y...