Real-Time Jamming DoS Detection in Safety-Critical V2V C-ITS Using Data Mining

A data-mining-based method for real-time detection of radio jamming denial-of-service attacks in the IEEE 802.11p vehicle-to-vehicle (V2V) communications is proposed. The method aims at understanding the reasons for losses of periodic cooperative awareness messages (CAMs) exchanged by vehicles in a platoon. Detection relies on a knowledge of the IEEE 802.11p protocol rules as well as on the historical observation of events in the V2V channel. In comparison with the state-of-the-art method, the proposed method allows operating under the realistic assumption of random jitter accompanying every CAM transmission. The method is evaluated for two jamming models: random and ON–OFF.

[1]  James Gross,et al.  Experimental Characterization and Modeling of RF Jamming Attacks on VANETs , 2015, IEEE Transactions on Vehicular Technology.

[2]  Yan Zhang,et al.  Evaluating Defence Schemes Against Jamming in Vehicle Platoon Networks , 2015, 2015 IEEE 18th International Conference on Intelligent Transportation Systems.

[3]  Jonathan Loo,et al.  Real-Time Detection of Denial-of-Service Attacks in IEEE 802.11p Vehicular Networks , 2014, IEEE Communications Letters.

[4]  Amir Alipour-Fanid,et al.  String Stability Analysis of Cooperative Adaptive Cruise Control under Jamming Attacks , 2017, 2017 IEEE 18th International Symposium on High Assurance Systems Engineering (HASE).

[5]  Peter Andres,et al.  Cooperative Intelligent Transport Systems in Europe: Current Deployment Status and Outlook , 2017, IEEE Vehicular Technology Magazine.

[6]  Vipin Kumar,et al.  Anomaly Detection for Discrete Sequences: A Survey , 2012, IEEE Transactions on Knowledge and Data Engineering.

[7]  Alexey V. Vinel,et al.  Vehicle-to-vehicle communication in C-ACC/platooning scenarios , 2015, IEEE Communications Magazine.

[8]  Cristofer Englund,et al.  Future Applications of VANETs , 2015 .