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.
Cite
@article{arxiv.2110.15650,
title = {RedCASTLE: Practically Applicable $k_s$-Anonymity for IoT Streaming Data at the Edge in Node-RED},
author = {Frank Pallas and Julian Legler and Niklas Amslgruber and Elias Grünewald},
journal= {arXiv preprint arXiv:2110.15650},
year = {2022}
}
Comments
Accepted for publication as regular research paper for the "8th International Workshop on Middleware and Applications for the Internet of Things". This is a preprint manuscript (authors' own version before final copy-editing)