Security and Privacy Analysis of Smartphone-Based Driver Monitoring Systems from the Developer's Point of View

Area of Science:

• Computer Science
• Cybersecurity
• Human-Computer Interaction

Background:

• Smartphone-based driver monitoring systems (DMS) present significant security and privacy risks due to their integration into critical transportation infrastructure.
• Existing methods lack automated analysis for DMS, especially in data-scarce environments, failing to address application-specific vulnerabilities.

Purpose of the Study:

• To propose an original, automated approach for the security and privacy analysis of smartphone-based driver monitoring systems.
• To provide developers with a tool to evaluate and enhance the security and privacy of their DMS products.

Main Methods:

• Utilizes white-box testing principles combined with a novel integration of various security and privacy analysis algorithms.
• Employs a modular and extensible framework designed to accommodate the specifics of smartphone-based DMS and operate with limited data.

Main Results:

• The approach successfully identifies security and privacy issues within a car driver monitoring use case.
• Provides actionable suggestions for issue mitigation and acknowledges analysis limitations due to data constraints.

Conclusions:

• The developed approach offers a practical solution for enhancing the security and privacy of smartphone-based DMS.
• It empowers developers to proactively address vulnerabilities, thereby improving the safety and reliability of modern vehicles.