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Privacy, GDPR, and Homomorphic Encryption

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IoT Platforms, Use Cases, Privacy, and Business Models

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Abstract

There is an increasing recognition of the value of personal data, and the extent of damage that can be caused if personal information is interfered with, released or stolen. Protection of personal data from unauthorised access or modification has been recognised in privacy regulations around the world. The European General Data Protection Regulation (GDPR) applies to anyone, or any organisation that handles personal data relating to a European citizen, irrespective of where in the world the data is held or used. Personal data includes information about an individual, their movements, or assets that can be associated with them directly, or by reference to other data files. Basic protection of privacy is achieved by using strong encryption to provide security of information (as described in Chap. 7), that is not sufficient. Personal data may be passed securely to a database, but who can access that database and what limits can be placed on their usage of those data? This chapter tries to answer to this and other important privacy-related questions. At the end of the chapter we introduce a reader with an architecture that limits the number of organisations and value-added service providers that can access personal data. The architecture was developed within the EU funded project VICINITY.

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Author information

Authors and Affiliations

  1. TU Kaiserslautern, Kaiserslautern, Germany

    Christopher Heinz, Alexander H. Wansch & Christoph Grimm

  2. Climate Associates Limited, Ipswich, UK

    Nigel Wall

Authors
  1. Christopher Heinz
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  2. Nigel Wall
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  3. Alexander H. Wansch
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  4. Christoph Grimm
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Corresponding author

Correspondence to Christopher Heinz .

Editor information

Editors and Affiliations

  1. Department of Computer Science, TU Kaiserslautern, Kaiserslautern, Germany

    Carna Zivkovic

  2. Department of Energy Technology, Aalborg University, Aalborg Øst, Denmark

    Yajuan Guan

  3. Department of Computer Science, TU Kaiserslautern, Kaiserslautern, Germany

    Christoph Grimm

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Heinz, C., Wall, N., Wansch, A.H., Grimm, C. (2021). Privacy, GDPR, and Homomorphic Encryption. In: Zivkovic, C., Guan, Y., Grimm, C. (eds) IoT Platforms, Use Cases, Privacy, and Business Models. Springer, Cham. https://doi.org/10.1007/978-3-030-45316-9_8

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  • DOI: https://doi.org/10.1007/978-3-030-45316-9_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-45315-2

  • Online ISBN: 978-3-030-45316-9

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