Author(s):
M. S. Maharajan, Hariharan Akshay Dev, Jeffrey Steve Paul S, Lakshmikanthan G, Chandru D, Dhanush Kodi R, Gopinathan M.
Email(s):
maha84rajan@gmail.com
DOI:
10.52711/2321-581X.2025.00008 
Address:
M. S. Maharajan*, Hariharan Akshay Dev, Jeffrey Steve Paul S, Lakshmikanthan G, Chandru D, Dhanush Kodi R, Gopinathan M.
Department of Artificial Intelligence & Data Science, Panimalar Engineering College, Chennai, 600123, India.
*Corresponding Author
Published In:
Volume - 16,
Issue - 2,
Year - 2025
ABSTRACT:
Modern cyber-attacks grow tougher that motivates the need for advanced protection methods. A real-time attack detection system operates through analysis of SIP signals by implementing CNN-based approaches according to the concept. The automated traffic analysis of the system uses a detection mechanism which detects potential attacks with both precision and speed. The CNN model uses network analysis to generate threat-based protection better than traditional signature approaches that need manual rulemaking. A dynamic real-time streaming system operates within the system framework to process SIP signals in real-time. The proposed detection approach succeeds in security tests which establishes exceptional results while reducing false warning occurrences. The approach works through deep learning techniques that promote automatic real-time attack detection which functions with high efficiency.
Cite this article:
M. S. Maharajan, Hariharan Akshay Dev, Jeffrey Steve Paul S, Lakshmikanthan G, Chandru D, Dhanush Kodi R, Gopinathan M.. Enhancing social media Integrity a Machine learning based rumor identification system utilizing CNN for accurate real time tweet analysis. Research Journal of Engineering and Technology. 2025; 16(2):80-0. doi: 10.52711/2321-581X.2025.00008
Cite(Electronic):
M. S. Maharajan, Hariharan Akshay Dev, Jeffrey Steve Paul S, Lakshmikanthan G, Chandru D, Dhanush Kodi R, Gopinathan M.. Enhancing social media Integrity a Machine learning based rumor identification system utilizing CNN for accurate real time tweet analysis. Research Journal of Engineering and Technology. 2025; 16(2):80-0. doi: 10.52711/2321-581X.2025.00008 Available on: https://ijersonline.org/AbstractView.aspx?PID=2025-16-2-4
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