Vehicular Communication Security: Multi-Channel and Multi-Factor Authentication
Fuente:
arXiv
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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866918014186684416 |
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| author | De Vincenzi, Marco Sun, Shuyang Zhang, Chen Bo Calvin Garcia, Manuel Ding, Shaozu Bodei, Chiara Matteucci, Ilaria Sarma, Sanjay E. Suo, Dajiang |
| author_facet | De Vincenzi, Marco Sun, Shuyang Zhang, Chen Bo Calvin Garcia, Manuel Ding, Shaozu Bodei, Chiara Matteucci, Ilaria Sarma, Sanjay E. Suo, Dajiang |
| contents | Secure and reliable communications are crucial for Intelligent Transportation Systems (ITSs), where Vehicle-to-Infrastructure (V2I) communication plays a key role in enabling mobility-enhancing and safety-critical services. Current V2I authentication relies on credential-based methods over wireless Non-Line-of-Sight (NLOS) channels, leaving them exposed to remote impersonation and proximity attacks. To mitigate these risks, we propose a unified Multi-Channel, Multi-Factor Authentication (MFA) scheme that combines NLOS cryptographic credentials with a Line-of-Sight (LOS) visual channel. Our approach leverages a challenge-response security paradigm: the infrastructure issues challenges and the vehicle's headlights respond by flashing a structured sequence containing encoded security data. Deep learning models on the infrastructure side then decode the embedded information to authenticate the vehicle. Real-world experimental evaluations demonstrate high test accuracy, reaching an average of 95% and 96.6%, respectively, under various lighting, weather, speed, and distance conditions. Additionally, we conducted extensive experiments on three state-of-the-art deep learning models, including detailed ablation studies for decoding the flashing sequence. Our results indicate that the optimal architecture employs a dual-channel design, enabling simultaneous decoding of the flashing sequence and extraction of vehicle spatial and locational features for robust authentication. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_00340 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Vehicular Communication Security: Multi-Channel and Multi-Factor Authentication De Vincenzi, Marco Sun, Shuyang Zhang, Chen Bo Calvin Garcia, Manuel Ding, Shaozu Bodei, Chiara Matteucci, Ilaria Sarma, Sanjay E. Suo, Dajiang Cryptography and Security Secure and reliable communications are crucial for Intelligent Transportation Systems (ITSs), where Vehicle-to-Infrastructure (V2I) communication plays a key role in enabling mobility-enhancing and safety-critical services. Current V2I authentication relies on credential-based methods over wireless Non-Line-of-Sight (NLOS) channels, leaving them exposed to remote impersonation and proximity attacks. To mitigate these risks, we propose a unified Multi-Channel, Multi-Factor Authentication (MFA) scheme that combines NLOS cryptographic credentials with a Line-of-Sight (LOS) visual channel. Our approach leverages a challenge-response security paradigm: the infrastructure issues challenges and the vehicle's headlights respond by flashing a structured sequence containing encoded security data. Deep learning models on the infrastructure side then decode the embedded information to authenticate the vehicle. Real-world experimental evaluations demonstrate high test accuracy, reaching an average of 95% and 96.6%, respectively, under various lighting, weather, speed, and distance conditions. Additionally, we conducted extensive experiments on three state-of-the-art deep learning models, including detailed ablation studies for decoding the flashing sequence. Our results indicate that the optimal architecture employs a dual-channel design, enabling simultaneous decoding of the flashing sequence and extraction of vehicle spatial and locational features for robust authentication. |
| title | Vehicular Communication Security: Multi-Channel and Multi-Factor Authentication |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2505.00340 |