Development of Security Starting System for Vehicles Based on IoT

Claude, Tuyisenge Jean; Viviane, Ishimwe; Paul, Iradukunda Jean; Mukanyiligira, Didacienne

doi:10.1109/icit52682.2021.9491637

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…They extracted different features related to steering and the accelerator, and classified different drivers with 85% accuracy. Meng et al [23] Other studies on anti-theft detection use facial recognition [24], vehicle security systems using IoT devices [25], and authenticated access control for vehicle systems using driving license and fingerprinting [26]. However, such solutions do not utilize artificial intelligence to train the system model.…”

Section: Related Workmentioning

confidence: 99%

ATVSA: Vehicle Driver Profiling for Situational Awareness

Khan

Saxena

Rana

et al. 2022

2022 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)

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Increasing connectivity and automation in vehicles leads to a greater potential attack surface. Such vulnerabilities within vehicles can also be used for auto-theft, increasing the potential for attackers to disable anti-theft mechanisms implemented by vehicle manufacturers. We utilize patterns derived from Controller Area Network (CAN) bus traffic to verify driver "behavior", as a basis to prevent vehicle theft. Our proposed model uses semi-supervised learning that continuously profiles a driver, using features extracted from CAN bus traffic. We have selected 15 key features and obtained an accuracy of 99% using a dataset comprising a total of 51 features across 10 different drivers. We use a number of data analysis algorithms, such as J48, Random Forest, JRip and clustering, using 94K records. Our results show that J48 is the best performing algorithm in terms of training and testing (1.95 seconds and 0.44 seconds recorded, respectively). We also analyze the effect of using a sliding window on algorithm performance, altering the size of the window to identify the impact on prediction accuracy.

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