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User-focused threat identification for anonymised microdata

Author

Listed:
  • Hans-Peter Hafner

    (Saarland State University of Applied Sciences)

  • Felix Ritchie

    (University of the West of England, Bristol)

  • Rainer Lenz

    (Technical University of Dortmund)

Abstract

When producing anonymised microdata for research, national statistics institutes (NSIs) identify a number of 'risk scenarios' of how intruders might seek to attack a confidential dataset. This paper argues that the strategy used to identify confidentiality protection measures can be seriously misguided, mainly since scenarios focus on data protection without sufficient reference to other aspects of data. This paper brings together a number of findings to see how the above problem can be addressed in a practical context. Using as an example the creation of a scientific use file, the paper demonstrates that an alternative perspective can have dramatically different outcomes.

Suggested Citation

  • Hans-Peter Hafner & Felix Ritchie & Rainer Lenz, 2015. "User-focused threat identification for anonymised microdata," Working Papers 20151503, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    • Handle: RePEc:uwe:wpaper:20151503
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    File URL: http://www2.uwe.ac.uk/faculties/BBS/BUS/Research/Economics%20Papers%202015/1503.pdf
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    References listed on IDEAS

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    1. Gail Pacheco & De Wet van der Westhuizen & Don J. Webber, 2012. "The changing influence of culture on job satisfaction across Europe: 1981-2008," Working Papers 2012-06, Auckland University of Technology, Department of Economics.
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    Citations

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    Cited by:

    1. Rainer Lenz, 2016. "Recent advances in cyclic perturbation of frequency tables [Neue Entwicklungen in der zyklischen Überlagerung von Fallzahltabellen]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(1), pages 37-62, February.
    2. Ritchie, Felix, 2017. "Spontaneous recognition: an unnecessary control on data access?," Statistics Paper Series 24, European Central Bank.
    3. Rainer Lenz, 2016. "Recent advances in cyclic perturbation of frequency tables," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(1), pages 37-62, February.
    4. Tanvi Desai & Felix Ritchie & Richard Welpton, 2016. "Five Safes: designing data access for research," Working Papers 20161601, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    5. Felix Ritchie & Jim Smith, 2019. "Confidentiality and linked data," Papers 1907.06465, arXiv.org.

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    More about this item

    Keywords

    statistical disclosure control; data protection; microdata anonymisation; big data;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

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