BSGI: An Effective Algorithm towards Stronger l-Diversity
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Publisher
Springer Berlin Heidelberg
Link
http://link.springer.com/content/pdf/10.1007/978-3-540-85654-2_3.pdf
Reference20 articles.
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4. Sweeney, L.: k-anonymity: a model for protecting privacy. International Journal on Uncertainty, Fuzziness, and Knowlege-Based Systems 10(5), 557–570 (2002)
5. Machanavajjhala, A., Gehrke, J., Kifer, D.: l-diversity: Privacy beyond k-anonymity. In: ICDE, p. 24 (2006)
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1. Maximum Entropy Oriented Anonymization Algorithm for Privacy Preserving Data Mining;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2012
2. eM2: An Efficient Member Migration Algorithm for Ensuring k-Anonymity and Mitigating Information Loss;Lecture Notes in Computer Science;2010
3. Decomposition: Privacy Preservation for Multiple Sensitive Attributes;Database Systems for Advanced Applications;2009
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