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Demo: LE3D: A Privacy-preserving Lightweight Data Drift Detection Framework. (arXiv:2211.01827v2 [cs.LG] UPDATED)
Nov. 22, 2022, 2:20 a.m. | Ioannis Mavromatis, Aftab Khan
cs.CR updates on arXiv.org arxiv.org
This paper presents LE3D; a novel data drift detection framework for
preserving data integrity and confidentiality. LE3D is a generalisable platform
for evaluating novel drift detection mechanisms within the Internet of Things
(IoT) sensor deployments. Our framework operates in a distributed manner,
preserving data privacy while still being adaptable to new sensors with minimal
online reconfiguration. Our framework currently supports multiple drift
estimators for time-series IoT data and can easily be extended to accommodate
new data types and drift detection …
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