A survey of social cybersecurity: Techniques for attack detection, evaluations, challenges, and future prospects
Author | Aos, Mulahuwaish |
Author | Qolomany, Basheer |
Author | Gyorick, Kevin |
Author | Abdo, Jacques Bou |
Author | Aledhari, Mohammed |
Author | Qadir, Junaid |
Author | Carley, Kathleen |
Author | Al-Fuqaha, Ala |
Available date | 2025-07-07T04:10:17Z |
Publication Date | 2025-05-31 |
Publication Name | Computers in Human Behavior Reports |
Identifier | http://dx.doi.org/10.1016/j.chbr.2025.100668 |
Citation | Mulahuwaish, A., Qolomany, B., Gyorick, K., Abdo, J. B., Aledhari, M., Qadir, J., ... & Al-Fuqaha, A. (2025). A survey of social cybersecurity: Techniques for attack detection, evaluations, challenges, and future prospects. Computers in Human Behavior Reports, 100668. |
ISSN | 24519588 |
Abstract | In today’s age of digital interconnectedness, understanding and addressing the nuances of social cybersecurity have become paramount. Unlike its broader counterparts, information security and cybersecurity, which are focused on safeguarding all forms of sensitive data and digital systems, social cybersecurity places its emphasis on the human and social dimensions of cyber threats. This field is uniquely positioned to address issues such as different social cybersecurity attacks like cyberbullying, cybercrime, spam, terrorist activities, and community detection. The significance of detection methods in social cybersecurity is underscored by the need for timely and proactive responses to these threats. In this comprehensive review, we delve into various techniques, attacks, challenges, potential solutions, and trends within the realm of detecting social cybersecurity attacks. Additionally, we explore the potential of readily available public datasets and tools that could expedite research in this vital domain. Our objective is not only to tackle the existing challenges but also to illuminate potential pathways for future exploration. Through this survey, our primary focus is to provide valuable insights into the rapidly evolving landscape of social cybersecurity. By doing so, we aim to assist researchers and practitioners in developing effective prediction models, enhancing defense strategies, and ultimately fostering a safer digital environment. |
Language | en |
Publisher | Elsevier |
Subject | Social cybersecurity Detection Social network analysis Dynamic network analysis |
Type | Article Review |
Volume Number | 18 |
Open Access user License | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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