%0 Conference Proceedings
%T PrivacyFrost2: A Efficient Data Anonymization Tool Based on Scoring Functions
%+ KDDI R&D Laboratories Inc. [Saitama]
%A Kiyomoto, Shinsaku
%A Miyake, Yutaka
%Z Part 2: 4th International Workshop on Security and Cognitive Informatics for Homeland Defense (SeCIHD 2014)
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B International Cross-Domain Conference and Workshop on Availability, Reliability, and Security (CD-ARES)
%C Fribourg, Switzerland
%Y Stephanie Teufel
%Y Tjoa A Min
%Y Ilsun You
%Y Edgar Weippl
%I Springer
%3 Availability, Reliability, and Security in Information Systems
%V LNCS-8708
%P 211-225
%8 2014-09-08
%D 2014
%R 10.1007/978-3-319-10975-6_16
%Z Computer Science [cs]Conference papers
%X 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.
%G English
%Z TC 5
%Z TC 8
%Z WG 8.4
%Z WG 8.9
%2 https://inria.hal.science/hal-01403997/document
%2 https://inria.hal.science/hal-01403997/file/978-3-319-10975-6_16_Chapter.pdf
%L hal-01403997
%U https://inria.hal.science/hal-01403997
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-TC8
%~ IFIP-LNCS-8708
%~ IFIP-CD-ARES
%~ IFIP-WG8-4
%~ IFIP-WG8-9