Privacy preservation based on full-domain generalization for incremental data publishing

© Springer Science+Business Media Singapore 2016. As data can be continuously collected and grow all the time with the enabling of advancement in IT infrastructure, the privacy protection mechanism which is designed for static data might not be able to cope with this situation effectively. In this p...

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Main Authors: Soontornphand T., Harnsamut N., Natwichai J.
Format: Book Series
Published: 2017
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84959097921&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/42289
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-422892017-09-28T04:26:19Z Privacy preservation based on full-domain generalization for incremental data publishing Soontornphand T. Harnsamut N. Natwichai J. © Springer Science+Business Media Singapore 2016. As data can be continuously collected and grow all the time with the enabling of advancement in IT infrastructure, the privacy protection mechanism which is designed for static data might not be able to cope with this situation effectively. In this paper, we present an incremental full-domain generalization based on k-anonymity model for incremental data publishing scenario. First, the characteristics of incremental data publishing for two releases is to be observed. Subsequently, we generalize the observation for the multiple data release problem. Then, we propose an effective algorithm to preserve the privacy of incremental data publishing. From the experiment results, our proposed approach is highly efficient as well as its effectiveness, privacy protection, is very close to the bruteforce algorithm generating the optimal solutions. 2017-09-28T04:26:19Z 2017-09-28T04:26:19Z 2016-01-01 Book Series 18761100 2-s2.0-84959097921 10.1007/978-981-10-0557-2_57 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84959097921&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/42289
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
description © Springer Science+Business Media Singapore 2016. As data can be continuously collected and grow all the time with the enabling of advancement in IT infrastructure, the privacy protection mechanism which is designed for static data might not be able to cope with this situation effectively. In this paper, we present an incremental full-domain generalization based on k-anonymity model for incremental data publishing scenario. First, the characteristics of incremental data publishing for two releases is to be observed. Subsequently, we generalize the observation for the multiple data release problem. Then, we propose an effective algorithm to preserve the privacy of incremental data publishing. From the experiment results, our proposed approach is highly efficient as well as its effectiveness, privacy protection, is very close to the bruteforce algorithm generating the optimal solutions.
format Book Series
author Soontornphand T.
Harnsamut N.
Natwichai J.
spellingShingle Soontornphand T.
Harnsamut N.
Natwichai J.
Privacy preservation based on full-domain generalization for incremental data publishing
author_facet Soontornphand T.
Harnsamut N.
Natwichai J.
author_sort Soontornphand T.
title Privacy preservation based on full-domain generalization for incremental data publishing
title_short Privacy preservation based on full-domain generalization for incremental data publishing
title_full Privacy preservation based on full-domain generalization for incremental data publishing
title_fullStr Privacy preservation based on full-domain generalization for incremental data publishing
title_full_unstemmed Privacy preservation based on full-domain generalization for incremental data publishing
title_sort privacy preservation based on full-domain generalization for incremental data publishing
publishDate 2017
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84959097921&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/42289
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