Cybersecurity Threat Detection on Social Media Using NLP and URL Intelligence.
Ms. Simran Shinde
, Prashant Agrahari , Dhonde Krish
Cybersecurity, Social Media, Phishing Detection, NLP, Malicious URLs, Machine Learning.
Social media has become deeply embedded in everyday life, supporting communication, education, business activities, and large-scale information exchange. While this openness allows users to connect easily and share content instantly, it also exposes social media platforms to a wide range of cyber threats. Phishing attempts, online scams, impersonation, and the circulation of malicious links are increasingly common. Rather than attacking systems directly, cybercriminals often focus on manipulating human behavior by creating a sense of urgency, trust, or curiosity. Existing protection methods such as manual content review and static blacklist-based filtering struggle to keep pace with the constantly evolving and informal nature of social media communication
"Cybersecurity Threat Detection on Social Media Using NLP and URL Intelligence.", JETNR - JOURNAL OF EMERGING TRENDS AND NOVEL RESEARCH (www.JETNR.org), ISSN:2984-9276, Vol.4, Issue 4, page no.b317-b323, April-2026, Available :https://rjpn.org/JETNR/papers/JETNR2604167.pdf
Volume 4
Issue 4,
April-2026
Pages : b317-b323
Paper Reg. ID: JETNR_233341
Published Paper Id: JETNR2604167
Downloads: 00037
Research Area: Science and Technology
Country: -, -, India
ISSN: 2984-9276 | IMPACT FACTOR: 9.87 Calculated By Google Scholar | ESTD YEAR: 2023
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.87 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: RJPN (IJPublication) Janvi Wave
