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Ontology-based negotiation and enforcement of privacy constraints in collaborative knowledge discovery

Tuovinen, Lauri orcid logoORCID: 0000-0002-7916-0255 and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2018) Ontology-based negotiation and enforcement of privacy constraints in collaborative knowledge discovery. In: 2nd International Workshop on Personal Analytics and Privacy, 10 Sept, 2018, Dublin, Ireland.

Many people could benefit from collecting and analyzing their own personal digital data, but most do not possess the necessary expertise to do so. Remote collaboration with knowledge discovery experts who do possess this expertise is a possible solution to this conundrum but raises a number of issues of its own, one of which is preserving the data owner's privacy. It is up to the data owner to decide how much data to share with a data analyst, but withholding too much will make the analyst unable to help the data owner effectively, so it is necessary to find a trade-off between these two conflicting interests. We propose a solution whereby the data requirements imposed by analysis tasks and the access restrictions imposed by privacy constraints are encoded formally using an ontology, enabling automatic detection of conflicts. Once a conflict has been identified, the data owner and the data analyst can negotiate a resolution, possibly by transforming the data using a method that makes it no longer sensitive from the data owner's perspective while sufficiently preserving its utility from the data analyst's perspective. Using such an ontology, data owners and data analysts tap into a knowledge base of privacy-preserving data transformations, each with known effects on the utility of the transformed data for analysis. This makes it easier to find an acceptable trade-off between privacy and utility in future collaborations.
Item Type:Conference or Workshop Item (Lecture)
Event Type:Workshop
Uncontrolled Keywords:knowledge discovery; data mining; personal data; privacy; collaborative systems; ontologies
Subjects:Computer Science > Artificial intelligence
Computer Science > Computer software
Computer Science > Lifelog
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > INSIGHT Centre for Data Analytics
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:EU Horizon 2020 - Marie Skłodowska-Curie, grant No. 746837, Science Foundation Ireland, Research Centres Programme. Grant No. 12/RC/2289
ID Code:22660
Deposited On:13 Sep 2018 11:10 by Lauri Tuovinen . Last Modified 13 Sep 2018 11:10

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