Secure Routine: A Routine-Based Algorithm for Drivers Identification
This addresses security challenges in transportation systems by enabling driver identification, but it appears incremental as it builds on existing machine learning techniques.
The paper tackles the problem of driver identification by proposing Secure Routine, a paradigm that uses driver's habits to distinguish the vehicle's owner from other drivers, and it outperforms three existing machine learning-based works in evaluation.
The introduction of Information and Communication Technology (ICT) in transportation systems leads to several advantages (efficiency of transport, mobility, traffic management). However, it may bring some drawbacks in terms of increasing security challenges, also related to human behaviour. As an example , in the last decades attempts to characterize drivers' behaviour have been mostly targeted. This paper presents Secure Routine, a paradigm that uses driver's habits to driver identification and, in particular, to distinguish the vehicle's owner from other drivers. We evaluate Secure Routine in combination with other three existing research works based on machine learning techniques. Results are measured using well-known metrics and show that Secure Routine outperforms the compared works.