Cyber Threat Intelligence Automation Using AI in the Financial Sector
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The cyber threats affecting the financial sector have become more advanced and need swift, automated threat intelligence. This article dwells upon the power of Artificial Intelligence, specifically Natural Language Processing (NLP) and Knowledge Graphs (KGs) to change Cyber Threat Intelligence (CTI) in banking. We experiment with entity-relation extraction, report generation and graph-based correlation with Large Language Models (LLMs). Such methods as AGIR, AttacKG, and K-CTIAA are techniques that automate CTI analysis with substantial improvements in performance. Experimental findings: The F1-scores are improved, and the time used in report generation reduced by up to 40 percent. In our research work, we have shown how AI-based CTI can help provide real-time structured threat information to empower FI to proactively reduce cyber risk effectively.
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