research-article

Enhanced (k,e)-anonymous for categorical data

Authors:

Surapon Riyana,

Noppamas Riyana,

Srikul NanthachumphuAuthors Info & Claims

ICSCA '17: Proceedings of the 6th International Conference on Software and Computer Applications

Pages 62 - 67

https://doi.org/10.1145/3056662.3056668

Published: 26 February 2017 Publication History

Abstract

Currently, the information is available in the organizations to gain more utilities together with some reason such as improving the strategy of organization, research, or etc.,. For this reason, the data holder cannot avoid to share some existing data-collecting of organization to be outside the scope. Hence, before the data is shared to be outside the scope of data-collecting, the data holder must be confidence the shared data cannot be re-identified to the owner again. The (k,e)-Anonymous is one of the most of prominent models in term of privacy preservation. However, the traditional (k,e)-Anonymous model is designed to support only the numeric-sensitive attribute. In the real-world, the domain of sensitive attribute can be other data domains such as the categorical-sensitive, ordinal-sensitive, or etc.,. Therefore, in this work, we propose the extended capability of (k,e)-Anonymous to supports the sensitive attribute that is the categorical data-type in conjunction with the DFS algorithm and the post-order traversal.

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Cited By

Orhpomma SMekthanavanh VSoukhavong SHomdoung NSasujit KRiyana S(2024)Model for Preserving Privacy Data in URL Query Strings2024 10th International Conference on Engineering, Applied Sciences, and Technology (ICEAST)10.1109/ICEAST61342.2024.10553830(57-60)Online publication date: 1-May-2024
https://doi.org/10.1109/ICEAST61342.2024.10553830
Riyana SRiyana N(2024)Ensuring Security and Privacy Preservation for the Publication of Rating DatasetsSN Computer Science10.1007/s42979-024-02690-y5:4Online publication date: 27-Mar-2024
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Riyana SRiyana NNanthachumphu S(2021)Privacy Preservation Techniques for Sequential Data ReleasingProceedings of the 12th International Conference on Advances in Information Technology10.1145/3468784.3470468(1-9)Online publication date: 29-Jun-2021
https://dl.acm.org/doi/10.1145/3468784.3470468
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Index Terms

Enhanced (k,e)-anonymous for categorical data
1. Security and privacy
  1. Human and societal aspects of security and privacy
    1. Privacy protections

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cover image ACM Other conferences

ICSCA '17: Proceedings of the 6th International Conference on Software and Computer Applications

February 2017

339 pages

ISBN:9781450348577

DOI:10.1145/3056662

Conference Chairs:
Vitaliy Mezhuyev
Universiti Malaysia Pahang, Malaysia
,
Luigi Benedicenti
University of Regina, Canada

Copyright © 2017 ACM.

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Publication History

Published: 26 February 2017

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ICSCA 2017

ICSCA 2017: 2017 6th International Conference on Software and Computer Applications

February 26 - 28, 2017

Bangkok, Thailand

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Cited By

Orhpomma SMekthanavanh VSoukhavong SHomdoung NSasujit KRiyana S(2024)Model for Preserving Privacy Data in URL Query Strings2024 10th International Conference on Engineering, Applied Sciences, and Technology (ICEAST)10.1109/ICEAST61342.2024.10553830(57-60)Online publication date: 1-May-2024
https://doi.org/10.1109/ICEAST61342.2024.10553830
Riyana SRiyana N(2024)Ensuring Security and Privacy Preservation for the Publication of Rating DatasetsSN Computer Science10.1007/s42979-024-02690-y5:4Online publication date: 27-Mar-2024
https://doi.org/10.1007/s42979-024-02690-y
Riyana SRiyana NNanthachumphu S(2021)Privacy Preservation Techniques for Sequential Data ReleasingProceedings of the 12th International Conference on Advances in Information Technology10.1145/3468784.3470468(1-9)Online publication date: 29-Jun-2021
https://dl.acm.org/doi/10.1145/3468784.3470468
Riyana SRiyana N(2021)A Privacy Preservation Model for RFID Data-Collections is Highly Secure and More Efficient than LKC-PrivacyProceedings of the 12th International Conference on Advances in Information Technology10.1145/3468784.3469853(1-11)Online publication date: 29-Jun-2021
https://dl.acm.org/doi/10.1145/3468784.3469853
Riyana SRiyana N(2021)Achieving Anonymization Constraints in High-Dimensional Data Publishing Based on Local and Global Data SuppressionsSN Computer Science10.1007/s42979-021-00936-73:1Online publication date: 23-Oct-2021
https://doi.org/10.1007/s42979-021-00936-7
Riyana SRiyana NSujinda W(2021)An Anatomization Model for Farmer Data CollectionsSN Computer Science10.1007/s42979-021-00740-32:5Online publication date: 23-Jun-2021
https://doi.org/10.1007/s42979-021-00740-3
Riyana S(2021)($$l^{p_1}, \ldots ,l^{p_n}$$)-Privacy: privacy preservation models for numerical quasi-identifiers and multiple sensitive attributesJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-020-02715-3Online publication date: 2-Jan-2021
https://doi.org/10.1007/s12652-020-02715-3
Riyana NRiyana SNanthachumphu SSittisung SDuangban D(2021)Privacy Violation Issues in Re-publication of Modification DatasetsIntelligent Computing and Optimization10.1007/978-3-030-68154-8_79(938-953)Online publication date: 8-Feb-2021
https://doi.org/10.1007/978-3-030-68154-8_79
Lin GZhao HZhao LGan XYao Z(2020)Differential Privacy Information Publishing Algorithm based on Cluster Anonymity2020 International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE)10.1109/ICBAIE49996.2020.00054(226-233)Online publication date: Jun-2020
https://doi.org/10.1109/ICBAIE49996.2020.00054
Riyana SNanthachumphu SRiyana N(2020)Achieving Privacy Preservation Constraints in Missing-Value DatasetsSN Computer Science10.1007/s42979-020-00241-91:4Online publication date: 4-Jul-2020
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