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PKDD
2005
Springer
110views Data Mining» more  PKDD 2005»
13 years 11 months ago
k-Anonymous Patterns
It is generally believed that data mining results do not violate the anonymity of the individuals recorded in the source database. In fact, data mining models and patterns, in orde...
Maurizio Atzori, Francesco Bonchi, Fosca Giannotti...
VLDB
2005
ACM
136views Database» more  VLDB 2005»
13 years 11 months ago
On k-Anonymity and the Curse of Dimensionality
In recent years, the wide availability of personal data has made the problem of privacy preserving data mining an important one. A number of methods have recently been proposed fo...
Charu C. Aggarwal
ICDE
2007
IEEE
1577views Database» more  ICDE 2007»
15 years 5 months ago
t-Closeness: Privacy Beyond k-Anonymity and l-Diversity
The k-anonymity privacy requirement for publishing microdata requires that each equivalence class (i.e., a set of records that are indistinguishable from each other with respect to...
Ninghui Li, Tiancheng Li, Suresh Venkatasubramania...
ICDE
2008
IEEE
118views Database» more  ICDE 2008»
14 years 7 months ago
k-Anonymization Revisited
In this paper we introduce new notions of k-type anonymizations. Those notions achieve similar privacy goals as those aimed by Sweenie and Samarati when proposing the concept of k-...
Aristides Gionis, Arnon Mazza, Tamir Tassa
ICDE
2008
IEEE
219views Database» more  ICDE 2008»
14 years 7 months ago
Never Walk Alone: Uncertainty for Anonymity in Moving Objects Databases
Preserving individual privacy when publishing data is a problem that is receiving increasing attention. According to the k-anonymity principle, each release of data must be such th...
Osman Abul, Francesco Bonchi, Mirco Nanni