JOURNAL ARTICLE

AI-Driven Threat Intelligence in Security Operations Centers

Shahab ud deen, Shahab ud deen

Year: 2025 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

The research paper explores how Artificial Intelligence (AI), particularly Machine Learning (ML) and Natural Language Processing (NLP), enhances the performance and accuracy of Security Operations Centers (SOCs). Traditional rule-based systems are often too slow and limited to handle the growing volume and complexity of modern cyber threats. This paper presents an AI-driven framework that automates threat detection, reduces false positives, and enables proactive defense by learning from new data in real time. The study concludes that integrating AI technologies transforms SOCs from reactive systems into intelligent, adaptive, and efficient cybersecurity centers.

Keywords:
Key (lock) Security information and event management Cyber threats Applications of artificial intelligence Intrusion detection system

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Topics

Network Security and Intrusion Detection
Physical Sciences →  Computer Science →  Computer Networks and Communications
Cybercrime and Law Enforcement Studies
Physical Sciences →  Computer Science →  Information Systems
Information and Cyber Security
Physical Sciences →  Computer Science →  Information Systems

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