Automatic Driver Identification from In-Vehicle Network Logs

-- Data generated by cars is growing at an unprecedented scale. As cars gradually become part of the Internet of Things (IoT) ecosystem, several stakeholders discover the value of in-vehicle network logs containing the measurements of the multitude of sensors deployed within the car . This wealth of data is also expected to be exploitable by third parties for the purpose of profiling drivers in order to provide personalized, value-added services. Although several prior works have successfully demonstrated the feasibility of driver re-identification using the in-vehicle network data captured on the vehicle's CAN (Controller Area Network) bus, they inferred the identity of the driver only from known sensor signals (such as the vehicle's speed, brake pedal position, steering wheel angle, etc.) extracted from the CAN messages. However, car manufacturers intentionally do not reveal exact signal location and semantics within CAN logs. We show that the inference of driver identity is possible even with off-the-shelf machine learning techniques without reverse-engineering the CAN protocol. We demonstrate our approach on a dataset of 33 drivers and show that a driver can be re-identified and distinguished from other drivers with an accuracy of 75-85%. I NTRODUCTION Almost all vehicles in use nowadays are equipped with various on-board Electrical Control Units (ECUs), sensors and actuators measuring and controlling the vehicle's speed, acceleration, braking, fuel consumption, battery status, or tire pressure level, among others. Sensors attached to their respective ECUs, whose number ranges from 5 to a hundred per vehicle, continuously generate a vast amount of real-time data. In order to implement complex control tasks for traffic safety or passenger infotainment, these data are then transferred among ECUs and other nodes over the in-vehicle network, most commonly following the Controller Area Network (CAN bus) standard [1]. In addition to being used real-time for automotive control, data are also transferred to car manufacturers through Internet-connected devices or pre-installed modems every half to five minutes.