Open access repository

Home Open access repository

In 2014, we launched our open-access repository which offers full text access to conference proceedings from many of our events including the INC and HAISA series. These papers are free to access and distribute (subject to citing the source).

» Openaccess proceedings » Twelfth International Symposium on Human Aspects of Information Security & Assurance (HAISA 2018)

Twelfth International Symposium on Human Aspects of Information Security & Assurance (HAISA 2018)

Twelfth International Symposium on Human Aspects of Information Security & Assurance (HAISA 2018)
Dundee, Scotland, UK, August 29-31, 2018
ISBN: 978-0-244-40254-9

Title: Are Attributes on Social Media Platforms Usable for Assisting in the Automatic Detection of Identity Deception?
Author(s): Estee van der Walt, Jan Harm Petrus Eloff
Reference: pp57-66
Keywords: Cyber-security, identity deception, fake identities, social media, big data, Twitter
Abstract: Social Media Platforms (SMPs) allow any person to easily communicate with their friends or the general public at large. People can now be targeted at great scale, most often for malicious purposes. The mere fact that more people are using SMPs exposes more people to various forms of cyber threats such as cyber-bullying. The problem is that many of these cyber-attacks involve some form of identity deception, where the attackers lie about who they are. The solution proposed in this paper is to work towards developing a model for Identity Deception Detection (IDD) on SMPs by identifying and using metadata that is freely available on SMPs. This metadata includes attributes that describes a user account on an SMP. The aim is to use only these attributes, as opposed to the contents of a communication, for determining if people are lying about their identities. By discarding contents, an identity deception detection model can be developed with lower overhead. A prototype is discussed that runs an experiment using the metadata (attributes) that defines the identity of a user on an SMP. The results show promise for further research in developing solutions for assisting with the automatic detection of identity deception.
Download count: 89

How to get this paper:

Download a free PDF copy of this paperBuy this book at Lulu.com

PDF copy of this paper is free to download. You may distribute this copy providing you cite this page as the source.