Cyber-security : identity deception detection on social media platforms

Show simple item record Van der Walt, Estee Eloff, Jan H.P. Grobler, Jacomine 2018-09-14T06:19:30Z 2018-09
dc.description.abstract Social media platforms allow billions of individuals to share their thoughts, likes and dislikes in real-time, without any censorship. This freedom, however, comes at a cyber-security risk. Cyber threats are more difficult to detect in a cyber world where anonymity and false identities are ever-present. The speed at which these deceptive identities evolve calls for solutions to detect identity deception. Cyber-security threats caused by humans on social media platforms are widespread and warrant attention. This research posits a solution towards the intelligent detection of deceptive identities contrived by human individuals on social media platforms (SMPs). Firstly, this research evaluates machine learning models by using attributes such as the “profile image” found on SMPs. To improve on the results delivered by these models, past research findings from the field of psychology, such as that humans lie about their gender, are used. Newly engineered features such as “gender-derived-from-the-profile-image” are evaluated to grasp whether these features detect deception with greater accuracy. Furthermore, research results from detecting non-human (also known as bot) accounts are also leveraged to improve on the initial results. These machine learning results are lastly applied to a proposed model for the intelligent detection and interpretation of identity deception on SMPs. This paper shows that the cyber-security threat of identity deception can potentially be minimized, should the vulnerability in the current way of setting up user accounts on SMPs be re-engineered in the future. en_ZA
dc.description.department Computer Science en_ZA
dc.description.department Industrial and Systems Engineering en_ZA
dc.description.embargo 2019-09-01
dc.description.librarian hj2018 en_ZA
dc.description.uri en_ZA
dc.identifier.citation Van der Walt, E., Eloff, J.H.P. & Grobler, J. 2018, 'Cyber-security : identity deception detection on social media platforms', Computers & Security, vol. 78, pp. 76-89. en_ZA
dc.identifier.issn 0167-4048 (print)
dc.identifier.issn 1872-6208 (online)
dc.identifier.other 10.1016/j.cose.2018.05.015
dc.language.iso en en_ZA
dc.publisher Elsevier en_ZA
dc.rights © 2018 Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Computers and Security. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Computers and Security, vol. 78, pp. 76-89, 2018.doi : 10.1016/j.cose.2018.05.015. en_ZA
dc.subject Social media platform (SMP) en_ZA
dc.subject Cyber-security en_ZA
dc.subject Identity deception en_ZA
dc.subject Social media en_ZA
dc.subject Big data en_ZA
dc.subject Bots en_ZA
dc.subject Grooming en_ZA
dc.subject Shape memory effect en_ZA
dc.subject Social networking (online) en_ZA
dc.subject Security systems en_ZA
dc.subject Learning systems en_ZA
dc.subject Artificial intelligence (AI) en_ZA
dc.title Cyber-security : identity deception detection on social media platforms en_ZA
dc.type Postprint Article en_ZA

Files in this item

This item appears in the following Collection(s)

Show simple item record