AI-DRIVEN THREAT INTELLIGENCE FOR REAL-TIME NETWORK SECURITY OPTIMIZATION
Artificial Intelligence (AI) revolutionizes network security through advanced threat intelligence and automated response mechanisms. This article investigates the integration of AI-driven frameworks in cybersecurity, examining their impact on threat detection, incident response, and overall security posture. The article demonstrates significant improvements in security operations through a comprehensive analysis of enterprise implementations, including reduced false positives, enhanced threat detection accuracy, and streamlined incident response processes. The article presents a multi-layered framework incorporating data collection, analysis, decision-making, and response components, validated through multiple case studies across financial, healthcare, and e-commerce sectors. The findings highlight how AI-driven security solutions effectively address the limitations of traditional security approaches while introducing new considerations for implementation and optimization.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-11-20
- DOI
- https://doi.org/10.5281/zenodo.14191399
- Primary Topic
- Information and Cyber Security
- Type
- article
- Field-Weighted Citation Impact
- 0.00