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On the Analysis of Utility and Risk for Masked Data in Big Data: A Small Data Analysis
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Skövde Artificial Intelligence Lab (SAIL))ORCID iD: 0000-0002-0368-8037
2018 (English)In: Frontiers in Artificial Intelligence and Applications: Artificial Intelligence Research and Development / [ed] Zoe Falomir, Karina Gibert, Enric Plaza, IOS Press , 2018, Vol. 308, p. 200-209Conference paper, Published paper (Refereed)
Abstract [en]

Data privacy studies methods to ensure that disclosure of sensitive information does not take place. Masking methods are applied to databases prior to their release so that intruders cannot access sensitive information. Masking methods modify the data reducing its quality. Information loss measures have been defined to evaluate in what extent data is still useful for particular analysis. In the case of big data, masking data and evaluating its utility is a complex problem. In this paper we focus on information loss measurement and we explore if we can estimate or give bounds of information loss for large data sets using only random subsets of the whole data set.

Place, publisher, year, edition, pages
IOS Press , 2018. Vol. 308, p. 200-209
Series
Frontiers in Artificial Intelligence and Applications, ISSN 0922-6389, E-ISSN 1879-8314 ; 308
Keywords [en]
big data, correlation coefficients, data utility, Information loss, statistical databases, statistics, Data privacy, Risk assessment, Complex problems, Correlation coefficient, Data utilities, Information loss measures, Random subsets, Sensitive informations, Statistical database
National Category
Other Computer and Information Science Media Engineering
Research subject
Skövde Artificial Intelligence Lab (SAIL); INF301 Data Science; INF303 Information Security
Identifiers
URN: urn:nbn:se:his:diva-16353DOI: 10.3233/978-1-61499-918-8-200Scopus ID: 2-s2.0-85055285689ISBN: 9781614999171 (print)ISBN: 978-1-61499-918-8 (electronic)OAI: oai:DiVA.org:his-16353DiVA, id: diva2:1262607
Conference
CCIA 2018, 21st International Conference of the Catalan Association for Artificial Intelligence Catalonia, Spain, 8-10th October 2018
Available from: 2018-11-12 Created: 2018-11-12 Last updated: 2019-02-14Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
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  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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