A natural human language framework for digital forensic readiness in the public cloud

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dc.contributor.author Baror, S.O. (Stacey)
dc.contributor.author Venter, H.S. (Hein)
dc.contributor.author Adeyemi, Richard
dc.date.accessioned 2021-03-01T07:10:19Z
dc.date.issued 2021
dc.description.abstract Currently, about half of all global enterprises are adopting and using some form of cloud computing services. In cloud computing, potential digital evidence is distributed across multiple isolated virtual machine instances. Investigating deleted or inactive virtual instances of a cloud is a challenge to digital forensics, and the traditional methods of digital forensics are inadequate to address such digital forensic investigation. Users of the public cloud (whether a potential victim of a cyberattack, a cybercriminal or a digital forensic investigator) inherently communicate using natural human language in the form of sentences and semantics in document messaging such as texts, emails or instant messages. Consequently, natural human language interaction provides a unique identifier for cloud users. This study leverages the natural human language as an identifier to develop a novel digital forensic readiness (DFR) framework for cloud computing to detect cybercrime. The DFR framework comprises the integration of natural language processing techniques in designing a process that mimics a near real-time approach towards cybercrime detection in a cloud environment. Natural language understanding techniques are used to analyse textdata of users in the public cloud and textdata of reported cybercrimes to develop a DFR framework. In the preliminary formation of the DFR framework, the output shows that cybercrime attacks that are in progress in the form of textdata such as online documents, instant messages or emails within an organizational cloud domain can be identified, and potentially investigated swiftly, using the unique signature of users as identifiers. When adopted, the proposed DFR framework can minimize the time lapses in incident identification and reduce the subsequent investigation time of cybercrimes in the public cloud domain. en_ZA
dc.description.department Computer Science en_ZA
dc.description.embargo 2021-07-12
dc.description.librarian hj2021 en_ZA
dc.description.uri http://www.tandfonline.com/loi/tajf20 en_ZA
dc.identifier.citation Stacey O. Baror , Hein S. Venter & Richard Adeyemi (2021): A natural human language framework for digital forensic readiness in the public cloud, Australian Journal of Forensic Sciences, DOI: 10.1080/00450618.2020.1789742. NYP en_ZA
dc.identifier.issn 0045-0618 (print)
dc.identifier.issn 1834-562X (online)
dc.identifier.other 10.1080/00450618.2020.1789742
dc.identifier.uri http://hdl.handle.net/2263/78877
dc.language.iso en en_ZA
dc.publisher Taylor and Francis en_ZA
dc.rights © 2020 Australian Academy of Forensic Sciences. This is an electronic version of an article published in Australian Journal of Forensic Sciences, vol. , no. , pp. , 2021. doi : 10.1080/00450618.2020.1789742. Australian Journal of Forensic Sciences is available online at : http://www.tandfonline.com/loi/tajf20. en_ZA
dc.subject Cybercrime en_ZA
dc.subject Digital forensics en_ZA
dc.subject Lexicon en_ZA
dc.subject Natural human language en_ZA
dc.subject Corpus data en_ZA
dc.subject Cloud computing en_ZA
dc.subject Semantics en_ZA
dc.title A natural human language framework for digital forensic readiness in the public cloud en_ZA
dc.type Postprint Article en_ZA


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