Dynamic encryption based secure key management for Vehicle-to-Vehicle communication in autonomous driving.

Area of Science:

• Cybersecurity
• Network Engineering
• Automotive Technology

Background:

• Traditional encryption methods are unsuitable for dynamic autonomous vehicle networks due to frequent topology changes and limited resources.
• Secure Vehicle-to-Vehicle (V2V) communication is crucial for the safety and trustworthiness of autonomous vehicles.

Purpose of the Study:

• To propose DASKM (Dynamic Autonomous Secure Key Management), a novel, lightweight solution for secure key management in V2V communication.
• To ensure data integrity and confidentiality in autonomous vehicle networks, even under high mobility rates.

Main Methods:

• DASKM employs a hierarchical and decentralized adaptive key management approach for real-time encryption key updates.
• Utilizes AES-128 in CTR mode and event-driven key rotation based on vehicle speed and proximity thresholds.
• Minimizes coordination overhead through pre-computed group keys for platoons.

Main Results:

• DASKM achieves computational overhead of 10-25 ms per packet, fitting within in-vehicle processing capabilities.
• Effectively defends against man-in-the-middle, replay, and spoofing attacks.
• Reduces latency by 30% and improves security response times by 25% compared to fixed models.

Conclusions:

• DASKM offers a practically scalable solution for securing V2V communication in autonomous vehicle networks.
• The adaptive key management protocol enhances network security, contributing to a safer autonomous driving future.
• Demonstrates scalability and stable performance in high-density fleet networks.