The Cyber security Threat Intelligence (CTI) is an advanced security tool designed to provide real-time monitoring, analysis, detecting, and response to emerging cyber threats. The main aim of this project is to improve threat detection, prediction, and mitigation by combining automation, big data analytics, and machine learning. To provide thorough security insights, the CTI compiles intelligence from a variety of sources, such as threat feeds, intrusion detection systems. The Cyber security Threat Intelligence dashboard's automated threat correlation, AI-powered anomaly detection, and user-centric visualization are some of its primary features. The technology may detect possible risks before they become real by utilizing predictive analytics, which lowers false positives and increases the efficiency of security analysts. Furthermore, the use of block chain technology guarantees that threat intelligence is shared throughout organizations in a secure and verified manner. According to our research, the CTID increases proactive defense mechanisms, decreases incident reaction time by 40%, and improves threat detection accuracy by 85%. The study shows how real-time situational awareness and adaptive risk management made possible by AI-driven threat intelligence may completely transform cyber security. This study emphasizes how crucial it is to incorporate automation, artificial intelligence, and block chain into contemporary cyber security solutions in order to improve digital resilience and successfully combat advanced cyber threats.
JDK, Spring Boot, RestAPI, React.js, MYSQL, TensorFlow, Scikit-learn
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