research-article

On Data Publishing with Clustering Preservation

Authors:

Michail Vlachos,

Johannes Schneider, and

Vassilios G. VassiliadisAuthors Info & Claims

ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 9, Issue 3

Article No.: 23, Pages 1 - 30

https://doi.org/10.1145/2700403

Published: 01 April 2015 Publication History

Abstract

The emergence of cloud-based storage services is opening up new avenues in data exchange and data dissemination. This has amplified the interest in right-protection mechanisms to establish ownership in the event of data leakage. Current right-protection technologies, however, rarely provide strong guarantees on dataset utility after the protection process. This work presents techniques that explicitly address this topic and provably preserve the outcome of certain mining operations. In particular, we take special care to guarantee that the outcome of hierarchical clustering operations remains the same before and after right protection. Our approach considers all prevalent hierarchical clustering variants: single-, complete-, and average-linkage. We imprint the ownership in a dataset using watermarking principles, and we derive tight bounds on the expansion/contraction of distances incurred by the process. We leverage our analysis to design fast algorithms for right protection without exhaustively searching the vast design space. Finally, because the right-protection process introduces a user-tunable distortion on the dataset, we explore the possibility of using this mechanism for data obfuscation. We quantify the tradeoff between obfuscation and utility for spatiotemporal datasets and discover very favorable characteristics of the process. An additional advantage is that when one is interested in both right-protecting and obfuscating the original data values, the proposed mechanism can accomplish both tasks simultaneously.

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Cited By

Abraham RSchneider Jvom Brocke J(2023)A taxonomy of data governance decision domains in data marketplacesElectronic Markets10.1007/s12525-023-00631-w33:1Online publication date: 22-May-2023
https://doi.org/10.1007/s12525-023-00631-w
Soltani Panah AYavari Avan Schyndel RGeorgakopoulos DYi X(2019)Context-Driven Granular Disclosure Control for Internet of Things ApplicationsIEEE Transactions on Big Data10.1109/TBDATA.2017.27374635:3(408-422)Online publication date: 1-Sep-2019
https://doi.org/10.1109/TBDATA.2017.2737463
Amiri FQuirchmayr G(2017)A comparative study on innovative approaches for privacy-preservation in knowledge discoveryProceedings of the 9th International Conference on Information Management and Engineering10.1145/3149572.3149586(120-127)Online publication date: 9-Oct-2017
https://dl.acm.org/doi/10.1145/3149572.3149586
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Index Terms

On Data Publishing with Clustering Preservation
1. Information systems
  1. Information retrieval
  2. Information systems applications
    1. Data mining

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Published In

cover image ACM Transactions on Knowledge Discovery from Data

ACM Transactions on Knowledge Discovery from Data Volume 9, Issue 3

TKDD Special Issue (SIGKDD'13)

April 2015

313 pages

ISSN:1556-4681

EISSN:1556-472X

DOI:10.1145/2737800

Editor:
Philip S. Yu
University of Illinois at Chicago, USA

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Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 01 April 2015

Accepted: 01 September 2014

Revised: 01 April 2014

Received: 01 November 2013

Published in TKDD Volume 9, Issue 3

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Cited By

Abraham RSchneider Jvom Brocke J(2023)A taxonomy of data governance decision domains in data marketplacesElectronic Markets10.1007/s12525-023-00631-w33:1Online publication date: 22-May-2023
https://doi.org/10.1007/s12525-023-00631-w
Soltani Panah AYavari Avan Schyndel RGeorgakopoulos DYi X(2019)Context-Driven Granular Disclosure Control for Internet of Things ApplicationsIEEE Transactions on Big Data10.1109/TBDATA.2017.27374635:3(408-422)Online publication date: 1-Sep-2019
https://doi.org/10.1109/TBDATA.2017.2737463
Amiri FQuirchmayr G(2017)A comparative study on innovative approaches for privacy-preservation in knowledge discoveryProceedings of the 9th International Conference on Information Management and Engineering10.1145/3149572.3149586(120-127)Online publication date: 9-Oct-2017
https://dl.acm.org/doi/10.1145/3149572.3149586
Yavari APanah AGeorgakopoulos DJayaraman PSchyndel R(2017)Scalable Role-Based Data Disclosure Control for the Internet of Things2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS.2017.307(2226-2233)Online publication date: Jun-2017
https://doi.org/10.1109/ICDCS.2017.307
Soltani Panah AVan Schyndel RSellis TBertino E(2016)On the Properties of Non-Media Digital Watermarking: A Review of State of the Art TechniquesIEEE Access10.1109/ACCESS.2016.25708124(2670-2704)Online publication date: 2016
https://doi.org/10.1109/ACCESS.2016.2570812

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