Scott, Emma, Panda, Sakshyam, Loukas, George ORCID: https://orcid.org/0000-0003-3559-5182 and Panaousis, Emmanouil ORCID: https://orcid.org/0000-0001-7306-4062 (2022) Optimising user security recommendations for AI-powered smart-homes. In: 2022 IEEE Conference on Dependable and Secure Computing (DSC). IEEE. ISBN 9781665421416 (doi:10.1109/DSC54232.2022.9888829)

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Abstract

Research in the context of user awareness has shown that smart-home occupants often lack cybersecurity awareness even when it comes to frequently used technologies such as online social networks and email. To cope with the risks, smart-homes must be equipped with adequate cybersecurity measures besides the knowledge and time required by smart-home occupants to implement security measures. In this paper, we explore potential threats in AI-powered smart-homes and identify a list of cybersecurity controls required to mitigate their potential impact considering attack vectors, as well as the time and knowledge required to implement a control. We use optimisation to identify the best set of controls to minimise the risk exposure considering these metrics. Our comparative analysis against a random selection approach highlight that our approach is at least 25% better at minimising risk. Finally, we show how improved knowledge or time impacts the risk.

Item Type:	Conference Proceedings
Title of Proceedings:	2022 IEEE Conference on Dependable and Secure Computing (DSC)
Uncontrolled Keywords:	cybersecurity, smart-home, threats, control optimisation, risk assessment
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > Internet of Things and Security Research Centre (ISEC) Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	06 Oct 2022 14:13
URI:	http://gala.gre.ac.uk/id/eprint/35985

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