CIC IoV dataset 2024

Advancing realistic IDS approaches against DoS and spoofing attack in IoV CAN bus

The main goal of this research is to propose a realistic benchmark dataset to support the development of new cybersecurity solutions for internet of vehicles (IoV) operations. To accomplish this, five attacks were executed against the fully intact inner structure of a 2019 Ford car, complete with all Electronic Control Units (ECUs). However, the vehicle was rendered immobile and incapable of causing any potential harm or injuries. Hence, all attacks were carried out on the vehicle without endangering the car's driver or passengers.

These attacks are classified as spoofing and Denial-of-Service (DoS) and were carried out through the CAN-BUS protocol. This effort establishes a baseline complementary to existing contributions and supports researchers to propose new IoV solutions to strengthen the overall security using different techniques (e.g., Machine Learning - ML).

The main contributions are:

• This research focuses on addressing the critical gap in cybersecurity for IoVs by developing a comprehensive security dataset called CICIoV2024. The dataset is derived from extensive experiments conducted on the ECUs of a 2019 Ford vehicle, and provides a detailed view of intra-vehicular communications. This dataset can be used as a benchmark to advance cybersecurity solutions in IoV.
• The paper offers a comprehensive examination of different Machine Learning (ML) techniques. It showcases the effectiveness of these algorithms in identifying, avoiding, and reducing cyber-attacks in IoV systems. This analysis is crucial in improving the understanding and application of ML in the field of IoV cybersecurity.
• The research on Foundation for Future IoV Security sets a new benchmark in the field of IoV security. This paves the way for future explorations and opens up avenues for further optimization of ML models. The research also enables a deeper analysis of features in IoV cybersecurity and facilitates the integration of the CICIoV2024 dataset with broader smart city systems. By laying the groundwork for developing diverse datasets focusing on different vehicle models, it creates a strong foundation for future research on IoV security.