A Review on Cyberstalking Detection Using Machine Learning Techniques: Current Trends and Future Direction

A Review on Cyberstalking Detection Using Machine Learning Techniques: Current Trends and Future Direction
  IJETT-book-cover           
  
© 2022 by IJETT Journal
Volume-70 Issue-3
Year of Publication : 2022
Authors : Arvind Kumar Gautam, Abhishek Bansal
https://doi.org/10.14445/22315381/IJETT-V70I3P211

How to Cite?

Arvind Kumar Gautam, Abhishek Bansal, "A Review on Cyberstalking Detection Using Machine Learning Techniques: Current Trends and Future Direction," International Journal of Engineering Trends and Technology, vol. 70, no. 3, pp. 95-107, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I3P211

Abstract
Web-based media organizations and other web applications, for example, WhatsApp, Facebook, YouTube, Instagram, Twitter, have become more well known among individuals for data sharing, live occasions, news, exposure, publicity, and cybercrimes. The utilization of online media stages additionally offers major issues through cyberstalking, cyberbullying, and different kinds of digital provocation. Cyberstalking and cyberbullying are frequently utilized reciprocally and include the utilization of the web to follow or target somebody in the web-based world. Cyberstalking is a basic worldwide issue that influences instructive foundations, casualties, and the whole human culture that should be distinguished, recognized, revealed, and controlled appropriately for the security of clients in online media. Machine learning is the most well-known method for making the cyberstalking recognition model. Researchers have recommended different recognition procedures utilizing machine learning to control and battle cyberstalking in web-based media. In this paper, the study relates to some popular features extraction methods machine learning classifiers for text classification and explores the datasets used by the researchers. The study also focuses on reasonably determining the research gaps and the scope for improving cyberstalking detection. This paper will review some cyberstalking detection techniques using machine learning, analyze the performance of popular machine learning classifiers and finally explore the issues, challenges, recent trends, and future direction for cyberstalking detection techniques.

Keywords
Machine learning, Cyberstalking detection, Cyberbullying, Features extraction, Word embedding.

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