Demo: LE3D: A Privacy-preserving Lightweight Data Drift Detection Framework
Mavromatis, Ioannis, Khan, Aftab
–arXiv.org Artificial Intelligence
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 mechanisms. This demo will illustrate the functionality of LE3D under a real-world-like scenario.
arXiv.org Artificial Intelligence
Nov-18-2022
- Country:
- Europe > United Kingdom > England > Bristol (0.05)
- Genre:
- Research Report (0.40)
- Industry:
- Information Technology > Security & Privacy (0.73)
- Technology: