Privacy-Preserving Identifiers for IoT: A Systematic Literature Review

The Internet of Things (IoT) paves the way for smart applications such as in E-health, E-homes, transportation, or energy production. However, IoT technologies also pose privacy challenges for their users, as they allow the tracking and monitoring of the users' behavior and context. The EU Gene...

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Veröffentlicht in:IEEE access 2020, Vol.8, p.168470-168485
Hauptverfasser: Akil, Mahdi, Islami, Lejla, Fischer-Hubner, Simone, Martucci, Leonardo A., Zuccato, Albin
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Sprache:eng
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Zusammenfassung:The Internet of Things (IoT) paves the way for smart applications such as in E-health, E-homes, transportation, or energy production. However, IoT technologies also pose privacy challenges for their users, as they allow the tracking and monitoring of the users' behavior and context. The EU General Data Protection Regulation (GDPR) mandates data controller to follow a data protection by design and default approach by implementing for instance pseudonymity for achieving data minimisation. This paper provides a systematic literature review for answering the question of what types of privacy-preserving identifiers are proposed by the literature in IoT environments for implementing pseudonymity. It contributes with classifications and analyses of IoT environments for which privacy-preserving identifiers have been proposed and of the pseudonym types and underlying identity management architectures used. Moreover, it discusses trends and gaps in regard to addressing privacy trade-offs.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3023659