Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Achieving k-anonymity privacy protection using generalization and suppression
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Transforming data to satisfy privacy constraints
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Data Privacy through Optimal k-Anonymization
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Incognito: efficient full-domain K-anonymity
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Mondrian Multidimensional K-Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Privacy Protection: p-Sensitive k-Anonymity Property
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
Personalized privacy preservation
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
(α, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
K-anonymization incremental maintenance and optimization techniques
Proceedings of the 2007 ACM symposium on Applied computing
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
ICDT'05 Proceedings of the 10th international conference on Database Theory
Micro-aggregation-based heuristics for p-sensitive k-anonymity: one step beyond
PAIS '08 Proceedings of the 2008 international workshop on Privacy and anonymity in information society
A measure of variance for hierarchical nominal attributes
Information Sciences: an International Journal
A family of enhanced (L,α)-diversity models for privacy preserving data publishing
Future Generation Computer Systems
Extended k-anonymity models against sensitive attribute disclosure
Computer Communications
Secure distributed computation of anonymized views of shared databases
ACM Transactions on Database Systems (TODS)
A practical approximation algorithm for optimal k-anonymity
Data Mining and Knowledge Discovery
k-Concealment: An Alternative Model of k-Type Anonymity
Transactions on Data Privacy
Improving accuracy of classification models induced from anonymized datasets
Information Sciences: an International Journal
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Existing privacy regulations together with large amounts of available data have created a huge interest in data privacy research. A main research direction is built around the k-anonymity property. Several shortcomings of the k-anonymity model have been fixed by new privacy models such as p-sensitive k-anonymity, l-diversity, (α, k)-anonymity, and t-closeness. In this paper we introduce the Enhanced PK Clustering algorithm for generating p-sensitive k- anonymous microdata based on frequency distribution of sensitive attribute values. The p-sensitive k-anonymity model and its enhancement, extended p- sensitive k-anonymity, are described, their properties are presented, and two diversity measures are introduced. Our experiments have shown that the proposed algorithm improves several cost measures over existing algorithms.