Cyber-Risk Assessment for Autonomous Ships
dc.contributor.author | Tam, K | |
dc.contributor.author | Jones, Kevin | |
dc.date.accessioned | 2018-04-10T11:39:11Z | |
dc.date.issued | 2018-12-06 | |
dc.identifier.isbn | 978-1-5386-4683-0 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/11245 | |
dc.description.abstract |
As a 183.3 Billion industry controlling 90 % of all world trade, the shipping community is continuously looking for methods to increase profits while still considering human and environmental safety. As a result of developing technologies and policy that make autonomy a feasible solution, at least three separate organizations are aiming to produce and sail their first autonomous ships by 2020. Thus it is essential to begin assessing their cyber-risk profiles in order to rank and mitigate any vulnerabilities. As existing risk models for physical ship safety and autonomous cars do not adequately represent the unique nature of cyber-threats for autonomous vessels within the maritime sector, this article applies a model-based risk assessment framework named MaCRA which had previous only been used to model existing ships, not those of the near-future. | |
dc.format.extent | 1-8 | |
dc.language.iso | en | |
dc.publisher | IEEE | |
dc.subject | Prevention | |
dc.title | Cyber-Risk Assessment for Autonomous Ships | |
dc.type | conference | |
dc.type | Conference Proceeding | |
plymouth.author-url | https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000458747300025&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 | |
plymouth.date-start | 2018-06-11 | |
plymouth.date-finish | 2018-06-12 | |
plymouth.volume | 00 | |
plymouth.conference-name | Cyber Security | |
plymouth.publication-status | Published | |
plymouth.journal | 2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) | |
dc.identifier.doi | 10.1109/cybersecpods.2018.8560690 | |
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/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics/SoECM - Manual | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dc.publisher.place | Glasgow | |
dcterms.dateAccepted | 2018-03-31 | |
dc.rights.embargoperiod | Not known | |
rioxxterms.versionofrecord | 10.1109/cybersecpods.2018.8560690 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.licenseref.startdate | 2018-12-06 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract |