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On the complexity of optimal K-anonymity
Abstract
The technique of k-anonymization has been proposed in the literature as an alternative way to release public information, while ensuring both data privacy and data integrity. We prove that two general versions of optimal k-anonymization of relations are NP-hard, including the suppression version which amounts to choosing a minimum number of entries to delete from the relation. We also present a polynomial time algorithm for optimal k-anonymity that achieves an approximation ratio independent of the size of the database, when k is constant. In particular, it is a O(k log k)-approximation where the constant in the big-O is no more than 4, However, the runtime of the algorithm is exponential in k. A slightly more clever algorithm removes this condition, but is a O(k log m)-approximation, where m is the degree of the relation. We believe this algorithm could potentially be quite fast in practice.
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Cites
k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY
SWEENEY, L. (2002) · International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems · doi:10.1142/s0218488502001648 · Cited by 8,571
Cited by
L -diversity: Privacy beyond k -anonymity
Machanavajjhala, A., Kifer, D., Gehrke, J., & Venkitasubramaniam, M. (2007) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/1217299.1217302 · Cited by 3,617
t-Closeness: Privacy Beyond k-Anonymity and l-Diversity
Li, N., Li, T., & Venkatasubramanian, S. (2007) · 2007 IEEE 23rd International Conference on Data Engineering · doi:10.1109/icde.2007.367856 · Cited by 3,451
Privacy-preserving data publishing: A survey of recent developments
Fung, B. C. M., Wang, K., Chen, R., & Yu, P. S. (2010) · ACM Computing Surveys · doi:10.1145/1749603.1749605 · Cited by 1,704
Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms
Gedik, B., & Liu, L. (2008) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2007.1062 · Cited by 837
Estimating the success of re-identifications in incomplete datasets using generative models
Rocher, L., Hendrickx, J. M., & de Montjoye, Y.-A. (2019) · Nature Communications · doi:10.1038/s41467-019-10933-3 · Cited by 816
Metadata
- Authors
- Meyerson, A., & Williams, R.
- Venue
- Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
- Publisher
- ACM
- Published
- 2004-06-14
- Pages
- 223-228
- OpenAlex
- W2052806235
- Cited by
- 821
- References
- 1
- FWCI
- 21.69
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Meyerson, A., & Williams, R. (2004). On the complexity of optimal K-anonymity. Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems. https://doi.org/10.1145/1055558.1055591
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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