Papers › RedCASTLE: Practically Applicable kₛ-Anonymity for IoT Streaming Data at the Edge in Node-RED
RedCASTLE: Practically Applicable kₛ-Anonymity for IoT Streaming Data at the Edge in Node-RED
Frank Pallas, Julian Legler, Niklas Amslgruber, Elias Grünewald
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In this paper, we present RedCASTLE, a practically applicable solution for Edge-based kₛ-anonymization of IoT streaming data in Node-RED. RedCASTLE builds upon a pre-existing, rudimentary implementation of the CASTLE algorithm and significantly extends it with functionalities indispensable for real-world IoT scenarios. In addition, RedCASTLE provides an abstraction layer for smoothly integrating kₛ-anonymization into Node-RED, a visually programmable middleware for streaming dataflows widely used in Edge-based IoT scenarios. Last but not least, RedCASTLE also provides further capabilities for basic information reduction that complement kₛ-anonymization in the privacy-friendly implementation of usecases involving IoT streaming data. A preliminary performance assessment finds that RedCASTLE comes with reasonable overheads and demonstrates its practical viability.
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