Methodology For Threat Detection and Prevention Integrating Cyber Threat Intelligence and Siem

Cyber threats, such as Advanced Persistent Threats (APTs), have evolved beyond the capabilities of traditional detection methods, necessitating more sophisticated solutions. This study presents an advanced methodology to enhance threat detection and prevention by integrating Cyber Threat Intelligence (CTI) with Security Information and Event Management (SIEM) systems. The proposed approach focuses on enriching threat intelligence with additional context and using SIEM platforms to identify malicious behavior by mapping Tactics, Techniques, and Procedures (TTPs). The integration between CTI and SIEM enhances detection capabilities by correlating security events with actionable intelligence, enabling faster identification of potential threats and improving the overall accuracy of incident response. Its effectiveness is demonstrated through case studies involving real malware samples, showing significant improvements in both detection speed and precision. Additionally, the study highlights the practical benefits of using enriched intelligence in real-time scenarios, emphasizing its value in proactive defense strategies. By advancing the integration between CTI and SIEM, this work provides a scalable framework for modern cybersecurity challenges, which could be further strengthened by incorporating NLP and LLMs, contributing to the global cybersecurity community’s efforts to combat evolving threats.