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AuthorAos, Mulahuwaish
AuthorQolomany, Basheer
AuthorGyorick, Kevin
AuthorAbdo, Jacques Bou
AuthorAledhari, Mohammed
AuthorQadir, Junaid
AuthorCarley, Kathleen
AuthorAl-Fuqaha, Ala
Available date2025-07-07T04:10:17Z
Publication Date2025-05-31
Publication NameComputers in Human Behavior Reports
Identifierhttp://dx.doi.org/10.1016/j.chbr.2025.100668
CitationMulahuwaish, 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.
ISSN24519588
URIhttps://www.sciencedirect.com/science/article/pii/S2451958825000831
URIhttp://hdl.handle.net/10576/65983
AbstractIn 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.
Languageen
PublisherElsevier
SubjectSocial cybersecurity
Detection
Social network analysis
Dynamic network analysis
TitleA survey of social cybersecurity: Techniques for attack detection, evaluations, challenges, and future prospects
TypeArticle Review
Volume Number18
Open Access user License http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.accessType Open Access


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