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Blurred Lines - A GDPR-Compliant Framework for Anonymising Automotive Video Data

USENIX via YouTube

Overview

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Learn about a GDPR-compliant framework for anonymizing automotive video data in this 20-minute conference presentation from VehicleSec '25. Discover how researchers from the University of Birmingham developed a comprehensive solution to protect personally identifiable information (PII) in vehicle-collected video feeds while maintaining compliance with General Data Protection Regulation requirements. Explore the framework's five distinct methods for identifying PII elements such as faces and license plates, along with various blurring approaches to mask sensitive information. Examine real-world testing results conducted with an industrial partner's dataset, demonstrating near 100% accuracy in detecting and anonymizing PIIs across different scenarios. Understand how this framework enables legal sharing of automotive video data between companies while preserving privacy protection. Review the tool's practical implementation features, including its user-friendly command-line interface and modular design that allows for future method additions, plus learn about its successful adaptation for industrial use.

Syllabus

VehicleSec '25 - WIP: Blurred Lines -- A GDPR-Compliant Framework for Anonymising Automotive...

Taught by

USENIX

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