Cyber Security Analytics: Human Vulnerability to Cyber Attack Attempts When Using Autonomous Vehicles

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Autonomous vehicles (AVs) promise huge benefits from improved road safety to reduced carbon emission. To reap the full benefit of such technology, future AVs have been envisioned to be "connected" in the sense that they will be able to communicate with each other and the external infrastructure through shared wireless networks so that optimisation of collective decision making can be achieved. This introduces new threats of cyber-attacks which could lead to severe disruptions to system operation and potentially cause catastrophic incidents. The most common infiltration/attack techniques (e.g., propagating malware across the entire network using spamming, malicious messaging and update requests) usually rely on the "cooperation" of the user of a terminal computer (e.g., accepting a request), which makes the human potentially the weakest link of the system if they succumb to such malicious attempts with data showing human error can be responsible for up to 95% of cyber security breaches. Human-factor-dependent cyber security vulnerabilities can be exacerbated in the context of autonomous driving - the low cognitive demand from the driving task may cause a lowered situation awareness and trigger an automatic, heuristic-driven cognitive processing style, which could make AV users more susceptible to falling victim of malicious spamming, as research shows.