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» Privacy-Preserving Data Imputation
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TDSC
2011
13 years 2 months ago
CASTLE: Continuously Anonymizing Data Streams
— Most of existing privacy preserving techniques, such as k-anonymity methods, are designed for static data sets. As such, they cannot be applied to streaming data which are cont...
Jianneng Cao, Barbara Carminati, Elena Ferrari, Ki...
AISADM
2007
Springer
14 years 1 months ago
Peer-to-Peer Data Mining, Privacy Issues, and Games
Peer-to-Peer (P2P) networks are gaining increasing popularity in many distributed applications such as file-sharing, network storage, web caching, searching and indexing of releva...
Kanishka Bhaduri, Kamalika Das, Hillol Kargupta
ICDM
2010
IEEE
150views Data Mining» more  ICDM 2010»
13 years 5 months ago
Probabilistic Inference Protection on Anonymized Data
Background knowledge is an important factor in privacy preserving data publishing. Probabilistic distributionbased background knowledge is a powerful kind of background knowledge w...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu, Ke Wang, Y...
CIKM
2009
Springer
14 years 3 days ago
A novel approach for privacy mining of generic basic association rules
Data mining can extract important knowledge from large data collections - but sometimes these collections are split among various parties. Privacy concerns may prevent the parties...
Moez Waddey, Pascal Poncelet, Sadok Ben Yahia
ICDM
2008
IEEE
95views Data Mining» more  ICDM 2008»
14 years 1 months ago
Publishing Sensitive Transactions for Itemset Utility
We consider the problem of publishing sensitive transaction data with privacy preservation. High dimensionality of transaction data poses unique challenges on data privacy and dat...
Yabo Xu, Benjamin C. M. Fung, Ke Wang, Ada Wai-Che...