The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Privacy Protection: p-Sensitive k-Anonymity Property
Abstract
In this paper, we introduce a new privacy protection property called p-sensitive k-anonymity. The existing kanonymity property protects against identity disclosure, but it fails to protect against attribute disclosure. The new introduced privacy model avoids this shortcoming. Two necessary conditions to achieve p-sensitive kanonymity property are presented, and used in developing algorithms to create masked microdata with p-sensitive k-anonymity property using generalization and suppression.
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Cites
UCI Repository of machine learning databases
Blake, C. L. (1998) · Medical Entomology and Zoology · Cited by 10,582
Protecting respondents identities in microdata release
Samarati, P. (2001) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/69.971193 · Cited by 2,324
ACHIEVING k-ANONYMITY PRIVACY PROTECTION USING GENERALIZATION AND SUPPRESSION
SWEENEY, L. (2002) · International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems · doi:10.1142/s021848850200165x · Cited by 1,976
Incognito: efficient full-domain K-anonymity
LeFevre, K., DeWitt, D. J., & Ramakrishnan, R. (2005) · Proceedings of the 2005 ACM SIGMOD international conference on Management of data · doi:10.1145/1066157.1066164 · Cited by 1,070
Health Insurance Portability and Accountability Act
(2007) · Encyclopedia of Measurement and Statistics · doi:10.4135/9781412952644.n199 · Cited by 969
Security-control methods for statistical databases: a comparative study
Adam, N. R., & Worthmann, J. C. (1989) · ACM Computing Surveys · doi:10.1145/76894.76895 · Cited by 969
UCI Repository of Machine Learning Database
Newman, D. J. (1998) · Medical Entomology and Zoology · Cited by 824
Privacy preserving mining of association rules
Evfimievski, A., Srikant, R., Agrawal, R., & Gehrke, J. (2002) · Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/775047.775080 · Cited by 768
Agrawal, R., Kiernan, J., Srikant, R., & Xu, Y. (2002) · VLDB '02: Proceedings of the 28th International Conference on Very Large Databases · doi:10.1016/b978-155860869-6/50021-4 · Cited by 723
Elements of Statistical Disclosure Control
Willenborg, L., & de Waal, T. (2001) · Lecture Notes in Statistics · doi:10.1007/978-1-4613-0121-9 · Cited by 649
Cited by
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
Metadata
- Authors
- Truta, T. M., & Vinay, B.
- Venue
- 22nd International Conference on Data Engineering Workshops (ICDEW'06)
- Publisher
- IEEE
- Published
- 2006
- Pages
- 94-94
- OpenAlex
- W2116241118
- Cited by
- 323
- References
- 15
- FWCI
- 13.21
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Truta, T. M., & Vinay, B. (2006). Privacy Protection: p-Sensitive k-Anonymity Property. 22nd International Conference on Data Engineering Workshops (ICDEW'06). https://doi.org/10.1109/icdew.2006.116
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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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