VetaDetect: Vehicle tampering detection with closed-loop model ensemble

Deliberate and unauthorized manipulations of vehicle components, also known as tampering, are nowadays affecting various vehicle functions. The European Commission, alongside several individual countries, estimated a growing number of tampered vehicles. Unfortunately, such manipulations are not detected in every case by the vehicle’s diagnostic system. In fact, modern tampering techniques are getting more complex, and are capable of emulating real signals via custom control devices. This paper proposes VetaDetect, a comprehensive methodology for the detection of vehicle tampering. VetaDetect consists of an ensemble of multiple-input single-output (MISO) Auto Regressive Moving Average models (ARX) that are fused together in a closed loop scenario with the Dempster-Shafer (D-S) theory of evidence. A key feature of the closed lop detection methodology is that the degree of belief associated to each detector (i.e., ARX model) is adjusted according to the reported belief on tampering. As a result, minority reports on successful tampering detection can influence the outcome of the fusion. Experimental results are based on data collected from a EURO VI D N2 class truck in the Vehicle Emissions Heavy Duty chassis laboratory (VELA) at the Joint Research Centre in the context of a real-world AdBlue (Urea) emulator that is connected to the vehicle.

HALLER Piroska;  GENGE Bela;  FORLONI Fabrizio;  BALDINI Gianmarco;  CARRIERO Massimo;  FONTARAS Georgios; 

2022-04-19

ELSEVIER

JRC126939

1874-5482 (online),   

https://www.sciencedirect.com/science/article/pii/S1874548222000154,    https://publications.jrc.ec.europa.eu/repository/handle/JRC126939,   

10.1016/j.ijcip.2022.100525 (online),