Driver Attribution in Connected Cars

The Internet of Things (IoT) has a massive impact on society, and business and whilst the innovations of Cyber-Physical Systems (CPS) bring about economic and social opportunities they could pose significant challenges in the digital forensics domain. Connected Cars (CC), as a catalyst and disruptor technology introduce new threats but also opportunities to address some vehicle related crimes, such as carjacking. In this article and within the context of CCs’ digital forensic investigation, we set our scope to facilitate drivers’ attribution based on their unique characteristics extracted from in-car sensors which not only manifests the driving behaviour at a point in time but also detect the emergence of this pattern over time. This would establish a connection between the car and the driver while providing digital evidence. Therefore, we critically discuss the importance of driver attribution to support modern digital forensic investigation in addition to demonstrating the method used to perform data acquisition from existing in-car sensors. We argue that this process can be automated as part of the CC Artificial Intelligence (AI) system and present initial empirical findings to share further use cases for this approach.

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