Adaptive Human-Computer Interfaces for Cybersecurity Situational Awareness in Autonomous Vehicles

Abstract

Such human factors research on AHCIs depends very much on the context of use, including organizational cultures such as risk tolerances and communication patterns. This paper considers both, of particular importance for stakeholders from critical infrastructure sectors. Its chapter 1 is an introduction that includes a description of the CSA challenge and its importance in the topic of AHCIs and CSA for autonomous vehicles. Autonomous vehicles are designed to operate while interacting with physical environments and human passengers without direct human intervention. Control of a level 5 vehicle is typically achieved without such vehicle human intervention. However, a computer and any connected networks may be subject to hostile act threats leading to a risk of severe CCS breach.

The core objective of the Daschem project is to identify the extent to which user-centered design methods for tailoring adaptive human-computer interfaces (AHCIs) can significantly improve cybersecurity situational awareness (CSA) in autonomous vehicles for laypersons. To reach that objective, the project will co-create AHCIs with stakeholders, using advanced digital technologies in a mixed-reality environment powered by artificial intelligence for data enrichment, scenario generation, and real-time semi-supervised learning testing. The project will conduct empirical, exploratory human factors research on real user reactions to simulated cyber-attacks and AHCIs, as well as real scenarios of interest, and evaluate the results. The project will apply qualitative and quantitative research methods to evaluate if AHCIs induce laypersons to engage in cyber-hazard risk mitigation behaviors, better CSA, and ability to spot manipulative social engineering attack indicators, and provide responses in case of a threat.