التفاصيل البيبلوغرافية
| العنوان: |
Exploiting the Shape of CAN Data for In-Vehicle Intrusion Detection |
| المؤلفون: |
Tyree, Zachariah, Bridges, Robert A., Combs, Frank L., Moore, Michael R. |
| المصدر: |
Proceedings of IEEE Connected and Autonomous Vehicles Symposium, VTC 2018 |
| سنة النشر: |
2018 |
| المجموعة: |
Computer Science |
| مصطلحات موضوعية: |
Computer Science - Cryptography and Security |
| الوصف: |
Modern vehicles rely on scores of electronic control units (ECUs) broadcasting messages over a few controller area networks (CANs). Bereft of security features, in-vehicle CANs are exposed to cyber manipulation and multiple researches have proved viable, life-threatening cyber attacks. Complicating the issue, CAN messages lack a common mapping of functions to commands, so packets are observable but not easily decipherable. We present a transformational approach to CAN IDS that exploits the geometric properties of CAN data to inform two novel detectors--one based on distance from a learned, lower dimensional manifold and the other on discontinuities of the manifold over time. Proof-of-concept tests are presented by implementing a potential attack approach on a driving vehicle. The initial results suggest that (1) the first detector requires additional refinement but does hold promise; (2) the second detector gives a clear, strong indicator of the attack; and (3) the algorithms keep pace with high-speed CAN messages. As our approach is data-driven it provides a vehicle-agnostic IDS that eliminates the need to reverse engineer CAN messages and can be ported to an after-market plugin. |
| نوع الوثيقة: |
Working Paper |
| URL الوصول: |
http://arxiv.org/abs/1808.10840 |
| رقم الانضمام: |
edsarx.1808.10840 |
| قاعدة البيانات: |
arXiv |