Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
On the design and quantification of privacy preserving data mining algorithms
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Practical Data-Oriented Microaggregation for Statistical Disclosure Control
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
Privacy-preserving k-means clustering over vertically partitioned data
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy-preserving Bayesian network structure computation on distributed heterogeneous data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Bottom-Up Generalization: A Data Mining Solution to Privacy Protection
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Top-Down Specialization for Information and Privacy Preservation
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Data Privacy through Optimal k-Anonymization
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
On the complexity of optimal K-anonymity
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Incognito: efficient full-domain K-anonymity
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
On k-anonymity and the curse of dimensionality
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Ordinal, Continuous and Heterogeneous k-Anonymity Through Microaggregation
Data Mining and Knowledge Discovery
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Achieving anonymity via clustering
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Maintaining data privacy in association rule mining
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
ICDT'05 Proceedings of the 10th international conference on Database Theory
A k-Anonymity Clustering Method for Effective Data Privacy Preservation
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Privacy preserving serial data publishing by role composition
Proceedings of the VLDB Endowment
A Novel Heuristic Algorithm for Privacy Preserving of Associative Classification
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
(α, k)-anonymous data publishing
Journal of Intelligent Information Systems
Incremental privacy preservation for associative classification
Proceedings of the ACM first international workshop on Privacy and anonymity for very large databases
Achieving k-anonymity via a density-based clustering method
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
Anonymization of moving objects databases by clustering and perturbation
Information Systems
FAANST: fast anonymizing algorithm for numerical streaming data
DPM'10/SETOP'10 Proceedings of the 5th international Workshop on data privacy management, and 3rd international conference on Autonomous spontaneous security
PCTA: privacy-constrained clustering-based transaction data anonymization
Proceedings of the 4th International Workshop on Privacy and Anonymity in the Information Society
On guaranteeing k-anonymity in location databases
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
Preserving privacy of moving objects via temporal clustering of spatio-temporal data streams
Proceedings of the 4th ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS
Utility-guided Clustering-based Transaction Data Anonymization
Transactions on Data Privacy
Priority driven k-anonymisation for privacy protection
AusDM '08 Proceedings of the 7th Australasian Data Mining Conference - Volume 87
A general framework for privacy preserving data publishing
Knowledge-Based Systems
MAGE: A semantics retaining K-anonymization method for mixed data
Knowledge-Based Systems
Journal of Computer Security
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Individual privacy will be at risk if a published data set is not properly de-identified. k-anonymity is a major technique to de-identify a data set. A more general view of k-anonymity is clustering with a constraint of the minimum number of objects in every cluster. Most existing approaches to achieving k-anonymity by clustering are for numerical (or ordinal) attributes. In this paper, we study achieving k-anonymity by clustering in attribute hierarchical structures. We define generalisation distances between tuples to characterise distortions by generalisations and discuss the properties of the distances. We conclude that the generalisation distance is a metric distance. We propose an efficient clustering-based algorithm for k-anonymisation. We experimentally show that the proposed method is more scalable and causes significantly less distortions than an optimal global recoding k-anonymity method.