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Cybersecurity Research

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Social Media User Relationship Framework (SMURF)

Journal of Digital Forensics, Security and Law

Volume 16, Article 1

2-16-2021

Anne David

Cranfield University, a.david ‘at’ cranfield.ac.uk

Sarah Morris

Cranfield University, s.l.morris ‘at’ cranfield.ac.uk

Gareth Appleby-Thomas

Cranfield University, g.thomas ‘at’ cranfield.ac.uk

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Recommended Citation David, Anne; Morris, Sarah; and Appleby-Thomas, Gareth (2021) “Social Media User Relationship Framework (SMURF),” Journal of Digital Forensics, Security and Law: Vol. 16 , Article 1. DOI: https://doi.org/10.15394/jdfsl.2021.1698 Available at: https://commons.erau.edu/jdfsl/vol16/iss1/1

This Article is brought to you for free and open access by the Journals at Scholarly Commons. It has been accepted for inclusion in Journal of Digital Forensics, Security and Law by an authorized administrator of Scholarly Commons. For more information, please contact [email protected]. (c)ADFSL

  1. Sarah Morris
  2. Gareth Appleby-Thomas
  3. ABSTRACT

ABSTRACT

The use of social media has spread through many aspects of society, allowing millions of individuals, corporate as well as government entities to leverage the opportunities it affords. These opportunities often end up being exploited by a small percentage of the user community who use it for objectionable or unlawful activities; for example, trolling, cyber bullying, grooming, luring. In some cases, these unlawful activities result in investigations where the swift retrieval of critical evidence is required in order to save a life. This paper presents a proof of concept (PoC) framework for social media user attribution. The framework aims to provide digital evidence that can be used to substantiate user activity in live triage investigations. This paper highlights the use of live triage as a viable technique for the investigation of social media activity, contextualizing user activity and attributing actions to users. It discusses the reliability of artefacts other than the communication content as a means of drawing inferences about user social media activity, taking into account.

Keywords: digital forensics, digital investigation, digital investigation framework, live triage, relationship attribution, social media

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