Mitigating Online Sexual Grooming Cybercrime on Social Media Using Machine Learning: A Desktop Survey

Abstract

Cyber threats such as identity deception, cyber bullying, identity theft and online sexual grooming have been witnessed on social media. These threats are disturbing to the society at large. Even more so to minors who are exposed to the Internet and might not even be aware of these threats. This paper describes a brief overview of different developments on cybersecurity methodologies that have been implemented to ensure safety of minors on social media, particularly; online sexual grooming. A desktop survey on Machine Learning technologies that have used to detect online sexual grooming is presented in this paper. The aim is to consolidate most of the work done in the past by scholars in this area of research, in order to develop insights on various algorithms that have been proposed and the reported performance results.