Situational awareness for trustworthy charging scenarios

Abstract

Growing acceptance of Electric Vehicles (EVs) by society is reshaping the transportation sector, which requires the development of robust charging infrastructures. Unfortunately, at present these infrastructures face multiple security challenges due to the complexities involved in integrating information systems with operational systems, which also leads to numerous security vulnerabilities and expands the attack surface. In response to this issue, this paper proposes a distributed Multi-Agent System (MAS) leveraging (i) smart consensus algorithms backed by Opinion Dynamics and (ii) blockchain technology to ensure trustworthy tracking of anomalies in EV charging networks based on the well-known Open Charge Point Protocol. The combined use of techniques and technologies streamlines diagnostic processes at charging stations, but also intensifies the vision (both local and global) necessary for greater protection. The monitoring method goes beyond the usual approaches, which typically focus on network traffic with a local context approach. It is capable of examining local health status related to anomalies found in individual devices, (i) analyzing each operational component and communication link, and (ii) contrasting actual perceptions with those perceived by the neighborhood. This way of broadening the security vision inherently contributes to situational awareness, explaining: where, what, or which components, devices, or charging zones are actually affected. This level of detail can even help ensure a more effective, efficient, and rapid responses depending on the situation.