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An Edge Framework for the Application of Privacy Enhancing Technologies in IoT Communications

: Kunz, I.; Stephanow, P.; Banse, C.


Institute of Electrical and Electronics Engineers -IEEE-:
IEEE International Conference on Communications, ICC 2020. Proceedings : Dublin, Ireland, 7 - 11 June 2020
Piscataway, NJ: IEEE, 2020
ISBN: 978-1-7281-5089-5
ISBN: 978-1-7281-5090-1
6 S.
International Conference on Communications (ICC) <2020, Online>
Fraunhofer AISEC ()

IoT devices generate large amounts of data that is often processed in cloud backends. This data, however, is often personal and sensitive. At the same time, IoT devices often communicate via edge devices that allow to pre-process the devices' data before it is sent to the cloud. To facilitate the privacy-preserving communication between IoT devices and cloud backends, we propose a framework that can be deployed on edge devices and which allows the application of Privacy Enhancing Technologies (PETs) and other computational tasks. It is designed as a practical tool for service providers supporting the privacy-friendly design and operation of edge-based services. It supports various stakeholder requirements, e.g. extendibility and auditability, as well as legal requirements which result from the General Data Protection Regulation (GDPR), e.g. data minimization. We also present an example application using the AWS IoT service and its Greengrass software to show how the framework can be used in a car-sharing service.