Trolling, Cyber-Stalking, Cyber-Bullying, and Identity Theft in OSNs

Abstract

Before the development of information and communication technology, social connections were confined by narrow cultural borders. User-generated multimodal information, online social networks, and rich data related to human behavior have all undergone a revolution as a result of these social technologies. However, the abuse of social technology, such as social media platforms, has given rise to a brand-new type of cyber-crimes such as cyberbullying, cyberstalking, cyber trolling, identity theft, etc. Such crimes result in a breach of privacy, a security lapse, financial fraud, and harm to public mental health and property. This chapter discusses various automated methods and systems driven by machine learning, deep learning, and fuzzy-logic-based algorithms for tackling various types of cybercrimes on various social media platforms. It then highlights various issues and challenges pertaining to the existing methods, which offer new study avenues for researchers to investigate.