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Self Adaptive Privacy in Cloud Computing Environments: Identifying the Major Socio-Technical Concepts

  • Conference paper
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Computer Security (CyberICPS 2020, SECPRE 2020, ADIoT 2020)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12501))

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Abstract

Privacy protection within Cloud Computing Environments (CCE) is extremely complex to be realized, due to multiple stakeholders’ interactions that lead to several privacy risks and leaks. Therefore, the necessity for self-adaptive privacy preserving schemes, in order to safeguard users’ privacy by considering their social and technological context within CCE is highlighted. Our analysis has indicated that a group of criteria should be satisfied in order to support this aim. However, it is pointed out that the criteria concerning the identification of users’ social needs and stakeholders’ technical privacy needs are not sufficiently satisfied, failing to determine which stakeholders’ privacy aspects should be examined and how. Towards this, the paper points out that Self Adaptive Privacy within CCE should be addressed as an emerged interdisciplinary research area, since the identified criteria concern both users’ social norms and technical privacy artifacts. Based on these criteria, the social and technical privacy aspects that should be considered from both users’ and developers’ perspective are discussed, leading to the identification of the socio-technical concepts and their interdependencies that should be taken into account. It proposes that a proper research design regarding Self Adaptive Privacy within CCE should be built, based on an interrelated three-layered examination that concerns users’, developers’ and CCE context, aiming to lay the ground for the identification of the Self-Adaptive Privacy related requirements within CCE.

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Acknowledgments

This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme “Human Resources Development, Education and Lifelong Learning 2014-2020” in the context of the project “Adaptive Privacy-aware Cloud-based Systems: Socio-technical requirements” (MIS:5047231)”.

Author information

Authors and Affiliations

  1. Privacy Engineering and Social Informatics Laboratory, Department of Cultural Technology and Communication, University of the Aegean, GR 81100, Lesvos, Greece

    Angeliki Kitsiou & Christos Kalloniatis

  2. Information and Communication Systems Security Laboratory, Department of Information and Communications Systems Engineering, University of the Aegean, GR 83200, Samos, Greece

    Eleni Tzortzaki

  3. Laboratory of Systems Security, Department of Digital Systems, University of Piraeus, GR 18532, Piraeus, Greece

    Stefanos Gritzalis

Authors
  1. Angeliki Kitsiou
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  2. Eleni Tzortzaki
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  3. Christos Kalloniatis
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  4. Stefanos Gritzalis
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Corresponding author

Correspondence to Angeliki Kitsiou .

Editor information

Editors and Affiliations

  1. Norwegian University of Science and Technology, Gjøvik, Norway

    Sokratis Katsikas

  2. Polytechnique Montréal, Montréal, QC, Canada

    Frédéric Cuppens

  3. Polytechnique Montréal, Montréal, QC, Canada

    Nora Cuppens

  4. University of Piraeus, Piraeus, Greece

    Costas Lambrinoudakis

  5. University of the Aegean, Mytilene, Greece

    Christos Kalloniatis

  6. Department of Computer Science, University of Toronto, Toronto, ON, Canada

    John Mylopoulos

  7. Georgia Institute of Technology, Atlanta, GA, USA

    Annie Antón

  8. University of Piraeus, Piraeus, Greece

    Stefanos Gritzalis

  9. Technical University of Denmark, Lyngby, Denmark

    Weizhi Meng

  10. University of Nottingham, Nottingham, UK

    Steven Furnell

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Kitsiou, A., Tzortzaki, E., Kalloniatis, C., Gritzalis, S. (2020). Self Adaptive Privacy in Cloud Computing Environments: Identifying the Major Socio-Technical Concepts. In: Katsikas, S., et al. Computer Security. CyberICPS SECPRE ADIoT 2020 2020 2020. Lecture Notes in Computer Science(), vol 12501. Springer, Cham. https://doi.org/10.1007/978-3-030-64330-0_8

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  • DOI: https://doi.org/10.1007/978-3-030-64330-0_8

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