arXiv:2606.28625v1 Announce Type: cross Abstract: Connected Vehicles (CVs) rely extensively on communication technologies to enable data-driven predictive analyses for enhancing performance and safety. These communication channels can be exploited by adversaries to launch cyberattacks such as Sybil attacks, which could threaten both safety-critical and mobility applications, leaving CVs vulnerable and putting human lives at risk. As CV deployment continues to expand, the need to detect and mitigate cyberattacks in real-time becomes increasingly urgent. This study presents an in-vehicle Digital
The proliferation of Connected Vehicles (CVs) and the increasing sophistication of cyber threats necessitate advanced security measures like Digital Twin-based detection frameworks.
Ensuring the integrity and security of autonomous and connected vehicle systems is crucial for public safety, the future of transportation, and the adoption of AI-driven mobility solutions.
The focus expands from purely functional vehicle performance to integrating robust cybersecurity and real-time threat detection within in-vehicle systems, utilizing advanced digital twin technology.
- · Cybersecurity firms specializing in automotive AI
- · Automotive OEMs prioritizing safety and security
- · Developers of digital twin technologies
- · Cybercriminals targeting CVs
- · Automotive companies with weak cybersecurity
- · Insurance providers facing increased liability from cyberattacks
Widespread adoption of digital twin technology for enhanced in-vehicle security and performance monitoring.
Increased regulatory scrutiny and standardization for cybersecurity in the connected and autonomous vehicle industry.
The development of a new market for 'cyber-secure by design' automotive components and integrated systems.
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