Towards Balancing Data Usefulness and Privacy Protection in K-Anonymisation
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[1] Pierangela Samarati,et al. Generalizing Data to Provide Anonymity when Disclosing Information , 1998, PODS 1998.
[2] Chris Clifton,et al. Privacy-preserving k-means clustering over vertically partitioned data , 2003, KDD '03.
[3] Philip S. Yu,et al. Top-down specialization for information and privacy preservation , 2005, 21st International Conference on Data Engineering (ICDE'05).
[4] Osmar R. Zaïane,et al. Privacy Preserving Clustering by Data Transformation , 2010, J. Inf. Data Manag..
[5] Hui Wang,et al. A novel generic clustering method based on spatial operations , 2006 .
[6] David J. DeWitt,et al. Mondrian Multidimensional K-Anonymity , 2006, 22nd International Conference on Data Engineering (ICDE'06).
[7] Catherine Blake,et al. UCI Repository of machine learning databases , 1998 .
[8] Vijay S. Iyengar,et al. Transforming data to satisfy privacy constraints , 2002, KDD.
[9] ASHWIN MACHANAVAJJHALA,et al. L-diversity: privacy beyond k-anonymity , 2006, 22nd International Conference on Data Engineering (ICDE'06).
[10] Philip S. Yu,et al. A Condensation Approach to Privacy Preserving Data Mining , 2004, EDBT.
[11] David J. DeWitt,et al. Incognito: efficient full-domain K-anonymity , 2005, SIGMOD '05.
[12] Roberto J. Bayardo,et al. Data privacy through optimal k-anonymization , 2005, 21st International Conference on Data Engineering (ICDE'05).
[13] Josep Domingo-Ferrer,et al. Ordinal, Continuous and Heterogeneous k-Anonymity Through Microaggregation , 2005, Data Mining and Knowledge Discovery.