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dc.contributor.authorBen Salamah, F
dc.contributor.authorPALOMINO, MARCO
dc.contributor.authorCraven, Matthew
dc.contributor.authorPapadaki, Maria
dc.contributor.authorFurnell, Steven
dc.date.accessioned2023-08-29T17:44:07Z
dc.date.available2023-08-29T17:44:07Z
dc.date.issued2023-08-24
dc.identifier.issn2076-3417
dc.identifier.issn2076-3417
dc.identifier.otherARTN 9595
dc.identifier.urihttps://pearl.plymouth.ac.uk/handle/10026.1/21267
dc.description.abstract

Formalizing the approach towards risk management on social media is critical for organizations. Regrettably, a review of the state-of-the-art on cybersecurity training highlighted that the existing frameworks are either too generic or too cumbersome to be adapted to different organizations and needs. Thus, we developed the Adaptive Cybersecurity Training Framework for Social Media Risks (ACSTF-SMR), a framework that incorporates social media cybersecurity policies and best practices. The ACSTF-SMR enables organizations, trainers, and policymakers to address the challenges posed by social media in a way that satisfies employees’ training needs and adjusts to their preferences. We tested the ACSTF-SMR with 38 case studies. Employees’ behaviors, learning, and responses after training were assessed, and feedback was gathered to improve the framework. Interviews with policymakers were held to gain insight into the enforcement of social media policies. We conclude that the ACSTF-SMR is a reliable option to mitigate social media threats within organizations.

dc.format.extent9595-9595
dc.languageen
dc.publisherMDPI AG
dc.subjectcybersecurity
dc.subjectadaptive training
dc.subjectsocial media
dc.subjecteducation
dc.titleAn Adaptive Cybersecurity Training Framework for the Education of Social Media Users at Work
dc.typejournal-article
dc.typeJournal Article
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:001060981200001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.issue17
plymouth.volume13
plymouth.publication-statusPublished online
plymouth.journalApplied Sciences
dc.identifier.doi10.3390/app13179595
plymouth.organisational-group|Plymouth
plymouth.organisational-group|Plymouth|Faculty of Science and Engineering
plymouth.organisational-group|Plymouth|Faculty of Science and Engineering|School of Engineering, Computing and Mathematics
plymouth.organisational-group|Plymouth|REF 2021 Researchers by UoA
plymouth.organisational-group|Plymouth|Users by role
plymouth.organisational-group|Plymouth|Users by role|Academics
plymouth.organisational-group|Plymouth|REF 2021 Researchers by UoA|UoA10 Mathematical Sciences
plymouth.organisational-group|Plymouth|REF 2021 Researchers by UoA|UoA11 Computer Science and Informatics
plymouth.organisational-group|Plymouth|REF 2021 Researchers by UoA|ZZZ Extended UoA 10 - Mathematical Sciences
dcterms.dateAccepted2023-08-23
dc.date.updated2023-08-29T17:44:07Z
dc.rights.embargodate2023-8-31
dc.identifier.eissn2076-3417
dc.rights.embargoperiodforever
rioxxterms.versionofrecord10.3390/app13179595


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