Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
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
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
Privacy-enhancing k-anonymization of customer data
Proceedings of the twenty-fourth 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
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
Achieving anonymity via clustering
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Injecting utility into anonymized datasets
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Personalized privacy preservation
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
A secure distributed framework for achieving k-anonymity
The VLDB Journal — The International Journal on Very Large Data Bases
Anatomy: simple and effective privacy preservation
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Privacy-preserving distributed k-anonymity
DBSec'05 Proceedings of the 19th annual IFIP WG 11.3 working conference on Data and Applications Security
Privacy-preserving anonymization of set-valued data
Proceedings of the VLDB Endowment
Towards trajectory anonymization: a generalization-based approach
SPRINGL '08 Proceedings of the SIGSPATIAL ACM GIS 2008 International Workshop on Security and Privacy in GIS and LBS
AlphaSum: size-constrained table summarization using value lattices
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
On the comparison of microdata disclosure control algorithms
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Privately detecting bursts in streaming, distributed time series data
Data & Knowledge Engineering
The union-split algorithm and cluster-based anonymization of social networks
Proceedings of the 4th International Symposium on Information, Computer, and Communications Security
Towards Trajectory Anonymization: a Generalization-Based Approach
Transactions on Data Privacy
Privacy-Preserving Data Publishing
Foundations and Trends in Databases
Privacy-preserving data publishing: A survey of recent developments
ACM Computing Surveys (CSUR)
Privacy-preserving data mining: A feature set partitioning approach
Information Sciences: an International Journal
Towards an axiomatization of statistical privacy and utility
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
ACM Transactions on Database Systems (TODS)
Local and global recoding methods for anonymizing set-valued data
The VLDB Journal — The International Journal on Very Large Data Bases
PCTA: privacy-constrained clustering-based transaction data anonymization
Proceedings of the 4th International Workshop on Privacy and Anonymity in the Information Society
Limiting disclosure of sensitive data in sequential releases of databases
Information Sciences: an International Journal
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
Utility-guided Clustering-based Transaction Data Anonymization
Transactions on Data Privacy
Privacy preservation by disassociation
Proceedings of the VLDB Endowment
A Knowledge Model Sharing Based Approach to Privacy-Preserving Data Mining
Transactions on Data Privacy
Fast clustering-based anonymization approaches with time constraints for data streams
Knowledge-Based Systems
Improving accuracy of classification models induced from anonymized datasets
Information Sciences: an International Journal
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k-Anonymity is a method for providing privacy protection by ensuring that data cannot be traced to an individual. In a k-anonymous dataset, any identifying information occurs in at least k tuples. To achieve optimal and practical k-anonymity, recently, many different kinds of algorithms with various assumptions and restrictions have been proposed with different metrics to measure quality. This paper evaluates a family of clustering-based algorithms that are more flexible and even attempts to improve precision by ignoring the restrictions of user-defined Domain Generalization Hierarchies. The evaluation of the new approaches with respect to cost metrics shows that metrics may behave differently with different algorithms and may not correlate with some applications' accuracy on output data.