AI-Driven Threat Intelligence in Security Operations Centers
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.
Institutions
- University of Wah (PK)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-11-03
- DOI
- https://doi.org/10.5281/zenodo.17512977
- Primary Topic
- Network Security and Intrusion Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00