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How secure is home: assessing human susceptibility to IoT threats

How secure is home: assessing human susceptibility to IoT threats

Parsons, Emily Kate, Panaousis, Emmanouil ORCID: 0000-0001-7306-4062 and Loukas, George ORCID: 0000-0003-3559-5182 (2020) How secure is home: assessing human susceptibility to IoT threats. In: PCI 2020: 24th Pan-Hellenic Conference on Informatics. ACM, pp. 64-71. ISBN 978-1450388979 (doi:https://doi.org/10.1145/3437120.3437277)

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Abstract

The use of Internet of Things (IoT) devices within the home has become more popular in recent years and with the COVID-19 pandemic more employees are working from home. Risk management has become decentralised, which is problematic for organisations since potential risks towards the company can not be controlled in a standardised and formal way. On the other side, users are suffering from smart home attacks due to the nature of IoT such as its heterogeneity and non-standardised architecture. However, the behaviour and attitudes of the user can dictate the increase or decrease of risk and possible losses due to the end user’s responsibility within the IoT life cycle. In this paper, we suggest that a user’s behaviour and attitude towards IoT devices within the smart home is imperative when designing a risk model for the home. We then consider the human element in the risk assessment process in IoT. We present a Smart Home Behaviour and Attitude Risk Model (SH-BARM) to discuss the importance of human behaviour and attitudes within the home and propose a solution to that will aid smart home inhabitants and organisations.

Item Type: Conference Proceedings
Title of Proceedings: PCI 2020: 24th Pan-Hellenic Conference on Informatics
Uncontrolled Keywords: security and privacy, human and societal aspects of security and privacy
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Liberal Arts & Sciences
Faculty of Liberal Arts & Sciences > Internet of Things and Security (ISEC)
Faculty of Liberal Arts & Sciences > School of Computing & Mathematical Sciences (CAM)
Last Modified: 27 Jul 2021 10:40
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/30254

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