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A hybrid anonymization pipeline to improve the privacy-utility balance in sensitive datasets for ML purposes

dc.contributor.authorVerdonck, Jenno
dc.contributor.authorDe Boeck, Kevin
dc.contributor.authorWillocx, Michiel
dc.contributor.authorLapon, Jorn
dc.contributor.authorNaessens, Vincent
dc.date.accessioned2024-03-25T16:10:35Z
dc.date.available2024-02-24T18:11:27Z
dc.date.available2024-03-25T16:10:35Z
dc.date.issued2023
dc.identifier.issnN/A
dc.identifier.otherWOS:001122662500010
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/43581.2
dc.sourceWOS
dc.titleA hybrid anonymization pipeline to improve the privacy-utility balance in sensitive datasets for ML purposes
dc.typeProceedings paper
dc.identifier.doi10.1145/3600160.3600168
dc.identifier.eisbn979-8-4007-0772-8
dc.source.numberofpages24
dc.source.peerreviewyes
dc.source.conference18th International Conference on Availability, Reliability and Security (ARES)
dc.source.conferencedateAUG 29-SEP 01, 2023
dc.source.conferencelocationBenevento
dc.source.journalN/A
imec.availabilityPublished - imec
dc.description.wosFundingTextThis research is partially funded by the VLAIO ICON project Co-CoNUT, the SOLIDLab Flanders initiative, and by the Flemish Re-search Programme Cybersecurity.


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220.500.12860/43581.2*2024-03-25T16:08:34Zvalidation by library/open access desk
120.500.12860/435812024-02-24T18:11:27Z

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