An Adaptive User Authentication Architecture for Drunk Driving and Vehicle Theft Mitigation

The high rate of vehicle theft and the loss of lives occasioned by drunk driving has caused irreparable losses to people and businesses, from a personal, commercial and reputation perspective. Existing systems deployed to mitigate against vehicle theft have all been breached by the ever-adaptive criminals. Drunk driving has been estimated to be a leading cause of deaths on highways and motorways, through preventable accidents. Technology has provided the tools that can aid in mitigating the vices aforementioned with the aim of provisioning lasting solutions. This paper proposes a new architecture for adaptive user authentication in order to mitigate drunk driving and vehicle theft. It considered user authentication in three (3) phases and proposed an authentication architecture for each identified phase, with a step by step description of the implementation method and tools for each phase. The architecture proposed in this study can aid in real time prevention of vehicular theft, unauthorized vehicular access and usage, while also utilizing the benefits of the latest technologies in machine vision and alcohol breadth analyzers to detect and prevent drunk driving, and the associated accidents it causes.