Doing cybersecurity at home: A human-centred approach for mitigating attacks in AI-enabled home devices

• To identify cyber-attacks on the AI, users must have some prior understanding of the AI parameters and their normativity. • Multimodal indicators embedded across the ecosystem of AI-enabled devices are an effective way in raising users’ attention to cyber-attacks. • Engaging users to actively diagnose and resolve cyber-attacks on AI-enabled devices in the home context must take into consideration the home routines, and be designed to avoid cognitive overload. • One way to minimise overload is to make use of users’ propensity to generalise their cybersecurity knowledge and skills where possible. AI-enabled devices are increasingly introduced in the home context and cyber-attacks targeting their AI component are becoming more frequent. Moving away from seeing the user as the problem to recognising the user as part of the solution, our research reports on a novel cybersecurity intervention (comprising Explainable AI features, assisted remediation) designed to support users to identify, diagnose and mitigate cyber-attacks on the AI component of their smart devices. We carried out a case study of a bespoke smart heating device inclusive of this intervention and conducted fieldwork with ten households who experienced simulated integrity cyber-attacks over a month. Our research contributes an understanding of how to design AI-enabled devices and their ecosystems to support users to perceive integrity cyber-attacks, offering new considerations for intervention design that exploits multimodal indicators and supports users to troubleshoot themselves the causes as well as actions of cyber-attacks. Contributing to the growing area of human-centred cybersecurity, we evidence the distinctive challenges users face when evaluating integrity attacks on the AI component in the home context.