journal article·2025-05-16Open access

Threat Analysis and Risk Assessment of a Driver Monitoring System

Marco De Santis, Edmund Jochim, Iulia-Cristiana Șodinca, Christian Esposito, Rahamatullah Khondoker

Applied Sciences· Volume 15· Issue 10

Abstract

The incorporation of Driver Monitoring Systems (DMSs) in vehicles is fundamental to enhancing road safety by continuously assessing driver behavior and identifying signs of fatigue or distraction. However, as these technologies evolve, they also present considerable cybersecurity challenges. This research undertakes an extensive Threat Analysis and Risk Assessment (TARA) of DMSs, adhering to the ISO/SAE 21434 standard, to methodically detect and assess potential security threats. A total of 115 threats were recognized and classified into 95 low-risk, 16 medium-risk, and 4 high-risk scenarios, underscoring key vulnerabilities in data transmission, sensor reliability, and communication frameworks. To mitigate these risks, we suggest a range of countermeasures, including enhanced encryption techniques, stringent authentication protocols, and reinforced access control mechanisms, designed to strengthen the security posture of DMSs in practical applications. This study introduces a structured framework for evaluating and addressing cybersecurity threats in alignment with industry regulations, facilitating the dependable and safeguarded implementation of DMSs in future vehicle architectures while contributing to ongoing progress in automotive cybersecurity.
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Research context

OpenAlex topics: Autonomous Vehicle Technology and Safety · Fire Detection and Safety Systems · Human-Automation Interaction and Safety

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Computer Science, University of Salerno, 84084 Fisciano, Italy

Department of CCCE, Faculty of IEM, THM University of Applied Sciences, 61169 Friedberg, Germany

Faculty of Automation and Computer Science, Politehnica University of Timișoara, 300223 Timisoara, Romania

Department of Business Informatics, Faculty of MND, THM University of Applied Sciences, 61169 Friedberg, Germany

Funding

European Commission

References (39)

Show source-provided references
1. Campos-Ferreira, A.E., Lozoya-Santos, J.d.J., Tudon-Martinez, J.C., Mendoza, R.A.R., Vargas-Martínez, A., Morales-Menendez, R., and Lozano, D. (2023). Vehicle and Driver Monitoring System Using On-Board and Remote Sensors. Sensors, 23.10.3390/s23020814 ↗
2. Driver Inattention Monitoring System for Intelligent Vehicles: A Review10.1109/TITS.2010.2092770 ↗
3. Securing the Future: A Comprehensive Review of Security Challenges and Solutions in Advanced Driver Assistance Systems10.1109/ACCESS.2023.3347200 ↗
4. A taxonomy of attack mechanisms in the automotive domain10.1016/j.csi.2021.103539 ↗
5. Countering Adversarial Attacks on Autonomous Vehicles Using Denoising Techniques: A Review10.1109/OJITS.2022.3142612 ↗
6. (2021). Road Vehicles—Cybersecurity Engineering (Standard No. ISO/SAE21434).
7. Su, Y.F., Hsu, C.Y., Wang, Y.C., and Yeh, C.Y. (2024). Image-Based Driver Status Monitoring System for Determining the Transfer of Dynamic Driving Tasks in Autonomous Vehicles, SAE International.10.4271/2024-01-2397 ↗
8. Joe, L.Y., Wang, N.N.P., Celine, K.K.Y., Regan, G.L.K., Hanafi, E., and Illias, H.A. (2023, January 8–10). IoT-Based Smart Driver Monitoring System With Emergency Response Mechanism. Proceedings of the 2023 Innovations in Power and Advanced Computing Technologies (i-PACT), Kuala Lumpur, Malaysia.10.1109/i-PACT58649.2023.10434713 ↗
9. Seat-Occupancy Detection System and Breathing Rate Monitoring Based on a Low-Cost mm-Wave Radar at 60 GHz10.1109/ACCESS.2021.3105390 ↗
10. Chen, Y., Luo, Y., Ma, J., Qi, A., Huang, R., de Paulis, F., and Qi, Y. (2023). Non-Contact In-Vehicle Occupant Monitoring System Based on Point Clouds from FMCW Radar. Technologies, 11.10.3390/technologies11020039 ↗
11. A Review on Drowsy Driving Detection Device Using Arduino and Eye-Blink Sensor
12. Ansari, H.R., Kordrostami, Z., and Mirzaei, A. (2023). In-vehicle wireless driver breath alcohol detection system using a microheater integrated gas sensor based on Sn-doped CuO nanostructures. Sci. Rep., 13.10.1038/s41598-023-34313-6 ↗
13. Pande, T., Shin, K., Prabhu, R., Muralidharan, N., Garud, H., Jagannathan, S., and Haas, S. (2024, January 6–8). Driver and Occupancy Monitoring Systems with AM62A. Proceedings of the 2024 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, USA.10.1109/ICCE59016.2024.10444397 ↗
14. Mishra, A., Kim, J., Kim, D., Cha, J., and Kim, S. (2020, January 21–24). An Intelligent In-cabin Monitoring System in Fully Autonomous Vehicles. Proceedings of the 2020 International SoC Design Conference (ISOCC), Yeosu, Republic of Korea.10.1109/ISOCC50952.2020.9333062 ↗
15. Vijay, A. (2023, January 29–31). Intelligent Driver Monitoring System for Safe Driving. Proceedings of the 2023 IEEE International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC), Venice, Italy.10.1109/ESARS-ITEC57127.2023.10114838 ↗
16. Thanikaiselvan, V. (2023, January 5–6). Driver Drowsiness Detection and Warning using Facial Features and Hand Gestures. Proceedings of the 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Vellore, India.
17. Elhawawsha, A., Zeine, C., Zeid Daou, R.A., Kalinowski, D., Khattar, J., Telawi, S., and Boercsoek, J. (2023, January 12–13). Design of a Novel Safe Approach to Monitor Drivers While Operating Their Cars. Proceedings of the 2023 Seventh International Conference on Advances in Biomedical Engineering (ICABME), Beirut, Lebanon.10.1109/ICABME59496.2023.10293128 ↗
18. Driver State Monitoring Technology for Conditionally Automated Vehicles: Review and Future Prospects
19. Heenetimulla, H.D.S.M., Das, S.K., Sahoo, G.K., and Singh, P. (2022, January 11–12). An FPGA System for Driver Mobile Usage Detection and Heart Rate-Based Health Monitoring. Proceedings of the 2022 2nd Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology (ODICON), Bhubaneswar, India.10.1109/ODICON54453.2022.10010243 ↗
20. Intelligent driver monitoring system: An Internet of Things-based system for tracking and identifying the driving behavior10.1016/j.csi.2022.103704 ↗
21. Wang, X., and Zhao, Q. (2022, January 25–27). A new method for monitoring the state of drivers-occupant based on infrared 3D camera. Proceedings of the 2022 China Automation Congress (CAC), Xiamen, China.10.1109/CAC57257.2022.10055849 ↗
22. Review and Perspectives on Human Emotion for Connected Automated Vehicles10.1007/s42154-023-00270-z ↗
23. Gebert, M., Kobiela, F., Leibinger, J., and Mueller, H. (2023, January 18–22). Towards In-vehicle Driver Fainting Detection. Proceedings of the Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Ingolstadt, Germany.10.1145/3580585.3607172 ↗
24. The Multimodal Driver Monitoring Database: A Naturalistic Corpus to Study Driver Attention10.1109/TITS.2021.3095462 ↗
25. Koch, K., Maritsch, M., van Weenen, E., Feuerriegel, S., Pfäffli, M., Fleisch, E., Weinmann, W., and Wortmann, F. (2023, January 23–28). Leveraging driver vehicle and environment interaction: Machine learning using driver monitoring cameras to detect drunk driving. Proceedings of the CHI ’23: CHI Conference on Human Factors in Computing Systems, Hamburg, Germany.10.2139/ssrn.4186589 ↗
26. Understanding occupants’ behaviour, engagement, emotion, and comfort indoors with heterogeneous sensors and wearables10.1038/s41597-022-01347-w ↗
27. Driver behavior detection and classification using deep convolutional neural networks10.1016/j.eswa.2020.113240 ↗
28. NVIDIA (2024). NVIDIA Jetson Xavier Series, NVIDIA. Available online: https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-xavier-series/.
29. NVIDIA Developer (2024). Deep Learning Accelerator (DLA), NVIDIA. Available online: https://developer.nvidia.com/deep-learning-accelerator.
30. A systematic review on detection and prediction of driver drowsiness
31. Wang, S., Hou, Y., Gao, F., and Ji, X. (2016, January 12–14). A novel IoT access architecture for vehicle monitoring system. Proceedings of the 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), Reston, VA, USA.10.1109/WF-IoT.2016.7845396 ↗
32. Shoup, V. (2025, May 12). A Proposal for an ISO Standard for Public Key Encryption (Version 2.1) 2002. Available online: https://www.shoup.net/papers/iso-2_1.pdf.
33. Nakhjiri, M., and Nakhjiri, M. (2005). AAA and Network Security for Mobile Access: Radius, Diameter, EAP, PKI and IP Mobility, Wiley.10.1002/0470017465 ↗
34. Designing and implementing an AUTOSAR-based Basic Software Module for enhanced security10.1016/j.comnet.2022.109377 ↗
35. European Parliament & Council of the European Union (2025, May 12). REGULATION (EU) 2016/ 679 of the European Parliament and of the Council—of 27 April 2016—on the protection of Natural Persons with Regard to the Processing of Personal Data and on the Free Movement of Such Data, and Repealing Directive 95/46/EC (General Data Protection Regulation). Available online: https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng.
36. A Comprehensive Survey on SSL/ TLS and their Vulnerabilities
37. (2025, May 12). Digital Signature Standard (DSS), Available online: https://nvlpubs.nist.gov/nistpubs/FIPS/NIST.FIPS.186-5.pdf.
38. Wagner, E., Bauer, J., and Henze, M. (2022, January 16–19). Take a Bite of the Reality Sandwich: Revisiting the Security of Progressive Message Authentication Codes. Proceedings of the WiSec ’22: 15th ACM Conference on Security and Privacy in Wireless and Mobile Networks, San Antonio, TX, USA.10.1145/3507657.3528539 ↗
39. Strengthening Automotive Cybersecurity: A Comparative Analysis of ISO/SAE 21434-Compliant Automatic Collision Notification (ACN) Systems10.3390/vehicles5040096 ↗