A Comprehensive Framework for Threat Intelligence-Driven Incident Detection - Baskaran, Saravanakumar (International Journal of Scientific Research and Management (IJSRM), 2019)
The increasing complexity of cybersecurity threats demands more advanced and intelligence-driven methods for incident detection. Traditional security measures are often reactive, leaving organizations vulnerable to sophisticated attacks. This article presents a comprehensive framework that integrates threat intelligence into incident detection processes, enhancing the ability to detect, respond to, and mitigate cyber threats in real-time. By leveraging actionable threat intelligence data, organizations can stay ahead of emerging threats and improve their overall cybersecurity posture. This framework highlights the use of machine learning models, data analytics, and automated incident response tools, ensuring efficient, real-time detection and minimizing false positives.