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International Conference on Trust and Privacy in Digital Business

TrustBus 2017: Trust, Privacy and Security in Digital Business pp 49–65Cite as

Pattern-Based Representation of Privacy Enhancing Technologies as Early Aspects

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10442))

Abstract

Several regulations and standards emphasize that privacy shall already be considered from the very beginning in software development. A crucial point during the development of a privacy-friendly software is the selection and integration of measures that implement specific privacy requirements or mitigate threats to these. These measures are called privacy enhancing technologies (PETs). PETs have a cross-cutting nature. That is, a PET needs often to be integrated into several base functionalities of the software-to-be. For example, anonymization techniques need to be integrated into functionalities that shall reveal originally identifiable information in an anonymized form to others. One possibility to handle cross-cutting concerns already on the requirements level is aspect-oriented requirements engineering. In this paper, we show how PETs can be represented as early aspects and how these can be integrated into a given requirements model in problem frames notation. Furthermore, we show how PETs can be represented as patterns to help requirements engineers to identify and select appropriate PETs that address the privacy requirements they have to satisfy. We use the PET Privacy-ABCs (Attribute-Based Credentials) to illustrate our approach.

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Notes

  1. 1.

    https://www.torproject.org/ Accessed 21 Mar 2017.

  2. 2.

    http://w3c.p3p.com Accessed 21 Mar 2017.

  3. 3.

    https://privacypatterns.org and https://privacypatterns.eu.

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Author information

Authors and Affiliations

  1. paluno - The Ruhr Institute for Software Technology, University of Duisburg-Essen, Duisburg, Germany

    Rene Meis & Maritta Heisel

Authors
  1. Rene Meis
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  2. Maritta Heisel
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Corresponding author

Correspondence to Rene Meis .

Editor information

Editors and Affiliations

  1. University of Malaga, Malaga, Spain

    Javier Lopez

  2. Karlstad University, Karlstad, Sweden

    Simone Fischer-Hübner

  3. University of Piraeus, Piraeus, Greece

    Costas Lambrinoudakis

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Meis, R., Heisel, M. (2017). Pattern-Based Representation of Privacy Enhancing Technologies as Early Aspects. In: Lopez, J., Fischer-Hübner, S., Lambrinoudakis, C. (eds) Trust, Privacy and Security in Digital Business. TrustBus 2017. Lecture Notes in Computer Science(), vol 10442. Springer, Cham. https://doi.org/10.1007/978-3-319-64483-7_4

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  • DOI: https://doi.org/10.1007/978-3-319-64483-7_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64482-0

  • Online ISBN: 978-3-319-64483-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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