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dc.contributor.authorMontasari, R.
dc.contributor.authorCarroll, Fiona
dc.contributor.authorJahankhani, H.
dc.contributor.authorHosseinian-Far, A.
dc.contributor.authorDaneshkhah, A.
dc.date.accessioned2020-10-23T13:20:22Z
dc.date.available2020-10-23T13:20:22Z
dc.date.issued2021-01-07
dc.identifier.citationMontasari, R. Fiona, C., Jahankhani, H., Hosseinian-Far, A. and Daneshkhah, A. (2021). Application of Artificial Intelligence and Machine Learning in Producing Actionable Cyber Threat Intelligence. In Montasari, R., Jahankhani, H. Hill, R. and Parkinson, S. (eds.) Digital Forensic Investigation of Internet of Things (IoT) Devices. Springer. pp. 47-64en_US
dc.identifier.isbn978-3-030-60424-0
dc.identifier.issn1613-5113
dc.identifier.urihttp://hdl.handle.net/10369/11184
dc.descriptionBook chapter in book series Advanced Sciences and Technologies for Security Applications: Digital Forensic Investigation of Internet of Things (IoT) Devices available at https://doi.org/10.1007/978-3-030-60425-7en_US
dc.description.abstractCyber Threat Intelligence (CTI) can be used by organisations to assist their security teams in safeguarding their networks against cyber-attacks. This can be achieved by including threat data feeds into their networks or systems. However, despite being an effective Cyber Security (CS) tool, many organisations do not sufficiently utilise CTI. This is due to a number of reasons such as not fully understanding how to manage a daily flood of data filled with extraneous information across their security systems. This adds an additional layer of complexity to the tasks performed by their security teams who might not have the appropriate tools or sufficient skills to determine what information to prioritise and what information to disregard. Therefore, to help address the stated issue, this paper aims firstly to provide an in-depth understanding of what CTI is and how it can benefit organisations, and secondly to deliver a brief analysis of the application of Artificial Intelligence and Machine Learning in generating actionable CTI. The key contribution of this paper is that it assists organisations in better understanding their approach to CTI, which in turn will enable them to make informed decisions in relation to CTI
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofseriesAdvanced Sciences and Technologies for Security Applications;
dc.titleApplication of Artificial Intelligence and Machine Learning in Producing Actionable Cyber Threat Intelligenceen_US
dc.typeBook chapteren_US
dc.identifier.doihttps://doi.org/10.1007/978-3-030-60425-7
dcterms.dateAccepted2020-07-20
rioxxterms.funderCardiff Metropolitan Universityen_US
rioxxterms.identifier.projectCardiff Metropolian (Internal)en_US
rioxxterms.versionNAen_US
rioxxterms.freetoread.startdate2100-01-01
rioxxterms.funder.project37baf166-7129-4cd4-b6a1-507454d1372een_US


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