Abstract :

The Rapid Increase In Cyberthreats Has Brought Attention To The Shortcomings Of Identification Methods Based On Rules And Signatures. Sophisticated, Context-aware Detection Algorithms Are Required Due To The Increasing Prevalence Of Hacks That Use Social Media, Complex Communication Channels, And Obfuscation Tactics. Natural Language Processing (NLP) And Artificial Intelligence (AI) Will Be Discussed In This Lecture Along With Their Historical Uses In Cyber Threat Detection. We Also Study Hybrid Systems, Such As Deep Neural Architectures (LSTM, CNN), Transformer-based Models (BERT, RoBERTa, GPT), And Ontologies And Knowledge Graphs. Using Examples From Social Media Conversations, Phishing Emails, And Unstructured Cyber Threat Intelligence (CTI) Reports, The Article Shows How Natural Language Processing (NLP) Can Be Used To Identify TTPs. It Also Tackles Problems With Clarity, Language Support, Real-time Operation, And Adequate Data. Lastly, It Talks About Recent Advancements That Point To A Move Toward Automated, Flexible, And User-friendly Security Systems. Large Language Models (LLMs), Explainable Artificial Intelligence, And Bidirectional Learning Are A Few Examples Of This. Keywords: Artificial Intelligence; Natural Language Processing (NLP); Cyber Threat Intelligence (CTI); Transformer Models; Deep Learning; Threat Profiling; Explainable AI; Phishing Detection; Named Entity Recognition; Cybersecurity Automation.

Published:

19-11-2025

Issue:

Vol. 25 No. 11 (2025)

Page Nos:

160-168

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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