Mac Dermott, AM, Kendrick, P, Idowu, IO, Ashall, M and Shi, Q (2019) Securing Things in the Healthcare Internet of Things. In: 2019 Global IoT Summit (GIoTS) . (Global IoT Summit, 17 June 2019 - 19 June 2019, Aarhus, Denmark).

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Abstract

The Internet of Things (IoT) has had a positive impact on e-health, assisted living, human-centric sensing and wellness. Recently this interconnection has been referred to as Healthcare IoT (H-IoT). Real-time monitoring based on the information gathered from the connected things provides large scale connectivity and a greater insight into patient care, individual habits and routines. While the benefits of introducing this paradigm into healthcare are conspicuous, the underlying security vulnerabilities and threats of the infrastructure and devices cannot go unaddressed. H-IoT is set to impact society significantly, and with attackers already exploiting the IoT in a myriad of ways, it is inevitable that the IoT will become the most vulnerable area of cyber security. Securing these 'things' in H-IoT requires a multi-faceted approach. A multi-agent approach to advanced persistent threat detection in networked systems is conveyed with the use of machine learning for predictive analytics: identifying security vulnerabilities, identifying patterns in order to make predictions and identify outliers.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords:	Healthcare; Cyber security; Internet of Things; Cloud computing; Fog computing
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Computer Science & Mathematics
Publisher:	IEEE
Date Deposited:	03 Jun 2019 09:18
Last Modified:	12 Jun 2024 12:17
DOI or ID number:	10.1109/GIOTS.2019.8766383
URI:	https://researchonline.ljmu.ac.uk/id/eprint/10770

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