• Moksha Patel
• Anusha PP

Cyber threats continuously evolve, making timely identification of malicious activities an important requirement for modern security monitoring. Threat Intelligence (TI) provides information about known malicious entities such as IP addresses, domains, and other Indicators of Compromise (IOCs), while anomaly detection helps identify suspicious behavior that may not be present in threat intelligence databases. This research presents a lightweight Threat Intelligence Feed Processor and Anomaly Detector designed for local security monitoring. The proposed system collects malicious IP indicators from an external threat intelligence source, processes and stores them in a SQLite database, and compares incoming network and log events against the stored indicators. Events that match known malicious indicators are identified as threats, while events without an IOC match are further examined using behavioral anomaly detection. The system generates alerts with low, medium, or high-risk levels and stores relevant evidence for analysis. A Flask-based dashboard provides centralized visibility into IOCs, alerts, network activity, system activity, evidence, and security scores. In the experimental implementation, 1,000 AbuseIPDB indicators were processed, resulting in a total IOC database containing 2,736 IP records. The system analyzed 16 unique IP addresses, generated seven security alerts, and detected five behavioral anomalies in a controlled environment. The results demonstrate that combining threat intelligence with behavioral analysis can provide a practical approach for local security monitoring.

Cyber Threat Intelligence, Threat Intelligence Feed, Indicators of Compromise, Anomaly Detection, Malicious IP Detection, Security Monitoring, Risk Scoring, Automated Threat Detection.

"Threat Intelligence Processing and Behavioral Anomaly Detection for Automated Security Monitoring", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 9, page no.d37-d45, September-2026, Available :http://www.jetir.org/papers/JETIR2609305.pdf

"Threat Intelligence Processing and Behavioral Anomaly Detection for Automated Security Monitoring", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 9, page no. ppd37-d45, September-2026, Available at : http://www.jetir.org/papers/JETIR2609305.pdf