Prem kumar@Shaktimaan

AI-powered cybersecurity threat detection system leveraging IBM Granite 3.1 and RAG to analyze security logs, detect anomalies, generate automated security reports, and suggest mitigation strategies. Designed for enterprise use with Linux CLI or web dashboard deployment. Our solution addresses the growing complexity of cybersecurity threats by integrating AI-driven analytics to identify patterns in vast security datasets. Using IBM Granite 3.1’s advanced NLP capabilities, we provide real-time threat intelligence, anomaly detection, and automated response recommendations. The system processes structured and unstructured data, ensuring compliance and scalability. With seamless integration into existing security frameworks, enterprises can enhance their cyber defense strategies efficiently. This solution ingests logs from various sources, cleans and normalizes the data, and applies AI-based threat detection to uncover malicious activities. It offers a high level of automation in generating security alerts and providing recommendations, reducing the workload on security teams. The RAG-based approach ensures that past incidents and security patterns inform new threat analysis, continuously improving the system’s accuracy. The project includes a user-friendly interface, either as a command-line tool for system administrators or a web dashboard for broader enterprise usability. The AI-driven system not only detects threats but also provides predictive analytics to forecast potential cyberattacks before they occur. Enterprises can leverage this technology to strengthen their security postures, minimize breaches, and improve incident response times. The deployment is designed for scalability and efficiency, our cybersecurity system offers an advanced approach to enterprise security, ensuring businesses stay ahead of evolving cyber threats.

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