A Survey on Cybercrime Using Social Media

Authors

  • Zainab Khyioon Abdalrdha Iraqi Commission for Computers and Informatics
  • Abbas Mohsin Al-Bakry University of Information Technology and Communications
  • Alaa K. Farhan University of Technology

DOI:

https://doi.org/10.25195/ijci.v49i1.404

Keywords:

Cybercrime, Deep learning, Crime detection, Social media, Natural Language Processing (NLP)

Abstract

There is growing interest in automating crime detection and prevention for large populations as a result of the increased usage of social media for victimization and criminal activities. This area is frequently researched due to its potential for enabling criminals to reach a large audience. While several studies have investigated specific crimes on social media, a comprehensive review paper that examines all types of social media crimes, their similarities, and detection methods is still lacking. The identification of similarities among crimes and detection methods can facilitate knowledge and data transfer across domains. The goal of this study is to collect a library of social media crimes and establish their connections using a crime taxonomy. The survey also identifies publicly accessible datasets and offers areas for additional study in this area.

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Author Biographies

Zainab Khyioon Abdalrdha, Iraqi Commission for Computers and Informatics

Informatics Institute of Postgraduate Studies

Alaa K. Farhan, University of Technology

Department of Computer Sciences

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Published

2023-06-11