Abstract : In this paper, we propose an anonymization scheme for generating a k-anonymous and l-diverse (or t-close) table, which uses three scoring functions, and we show the evaluation results for two different data sets. Our scheme is based on both top-down and bottom-up approaches for full-domain and partial-domain generalization, and the three different scoring functions automatically incorporate the requirements into the generated table. The generated table meets users’ requirements and can be employed in services provided by users without any modification or evaluation.
Type de document :
Communication dans un congrès
Stephanie Teufel; Tjoa A Min; Ilsun You; Edgar Weippl. International Cross-Domain Conference and Workshop on Availability, Reliability, and Security (CD-ARES), Sep 2014, Fribourg, Switzerland. Springer, Lecture Notes in Computer Science, LNCS-8708, pp.211-225, 2014, Availability, Reliability, and Security in Information Systems. 〈10.1007/978-3-319-10975-6_16〉
https://hal.inria.fr/hal-01403997
Contributeur : Hal Ifip
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Soumis le : lundi 28 novembre 2016 - 11:26:17
Dernière modification le : lundi 28 novembre 2016 - 11:36:46
Document(s) archivé(s) le : lundi 20 mars 2017 - 19:08:28
Shinsaku Kiyomoto, Yutaka Miyake. PrivacyFrost2: A Efficient Data Anonymization Tool Based on Scoring Functions. Stephanie Teufel; Tjoa A Min; Ilsun You; Edgar Weippl. International Cross-Domain Conference and Workshop on Availability, Reliability, and Security (CD-ARES), Sep 2014, Fribourg, Switzerland. Springer, Lecture Notes in Computer Science, LNCS-8708, pp.211-225, 2014, Availability, Reliability, and Security in Information Systems. 〈10.1007/978-3-319-10975-6_16〉. 〈hal-01403997〉
