Researchers have developed SPADE, a new dataset designed for deep learning-based intrusion detection systems focused on connected vehicle safety. SPADE addresses the vulnerability of Signal Phase and Timing (SPaT) messages, which are crucial for vehicles to understand intersection states. The dataset is generated through simulation, incorporating various attack classes and environmental conditions to provide a comprehensive resource for C-V2X security research. The SPADE dataset, along with its generation code and configurations, is publicly available on GitHub to promote reproducible research. AI
IMPACT This dataset could advance the development of more robust security systems for autonomous vehicles by enabling better deep learning-based threat detection.
RANK_REASON The item is a research paper published on arXiv detailing a new dataset for a specific security application. [lever_c_demoted from research: ic=1 ai=1.0]
- connected vehicle
- C-V2X security
- deep learning
- Eclipse MOSAIC
- GitHub
- intrusion detection systems
- SAE J2735
- Signal Phase and Timing (SPaT) messages
- SPADE
- Vehicle-to-Infrastructure (V2I)
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