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dc.contributor.authorLeister, W
dc.contributor.authorHamdi, M
dc.contributor.authorAbie, H
dc.contributor.authorPoslad, S
dc.date.accessioned2016-09-20T11:27:52Z
dc.date.issued2014
dc.date.issued2014-12-01
dc.date.submitted2015-12-09T00:26:46.928Z
dc.identifier.issn1942-2636
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/15455
dc.descriptionThe work presented here has been carried out in the project ASSET – Adaptive Security for Smart Internet of Things in eHealth (2012–2015) funded by the Research Council of Norway in the VERDIKT programme. W
dc.description.abstract—We present an assessment framework to evaluate adaptive security algorithms specifically for the Internet of Things (IoT) in eHealth applications. The successful deployment of the IoT depends on ensuring security and privacy, which need to adapt to the processing capabilities and resource use of the IoT. We develop a framework for the assessment and validation of context-aware adaptive security solutions for the IoT in eHealth that can quantify the characteristics and requirements of a situation. We present the properties to be fulfilled by a scenario to assess and quantify characteristics for the adaptive security solutions for eHealth. We then develop scenarios for patients with chronic diseases using biomedical sensors. These scenarios are used to create storylines for a chronic patient living at home or being treated in the hospital. We show numeric examples for how to apply our framework. We also present guidelines how to integrate our framework to evaluating adaptive security solutions
dc.description.sponsorshipThe work presented here has been carried out in the project ASSET – Adaptive Security for Smart Internet of Things in eHealth (2012–2015) funded by the Research Council of Norway in the VERDIKT programme.en_US
dc.format.extent93 - 109 (17)
dc.languageEnglish
dc.language.isoenen_US
dc.subjectInternet of Things
dc.subjectevaluation framework
dc.subjectscenarios
dc.subjectassessment
dc.subjecteHealth systems
dc.subjectadaptive security
dc.titleAn Evaluation Framework for Adaptive Security for the IoT in eHealth
dc.typeJournal Article
dc.rights.holder2014, © Copyright by authors, Published under agreement with IARIA -
dc.relation.isPartOfInt. J. on Advances in Security
dc.relation.isPartOfInternational Journal on Advances
pubs.issue3-4
pubs.organisational-group/Queen Mary University of London
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering/Electronic Engineering and Computer Science - Staff
pubs.publication-statusPublished
pubs.publisher-urlhttp://www.iariajournals.org/security/sec_v7_n34_2014_paged.pdf
pubs.volume7


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