MUMBAI, India, July 30 -- Intellectual Property India has published a patent application (202621067003 A) filed by Dr. Ashish Kumar Tamrakar; R. Ananthakrishnan; Dr. Shailendra. Pathare; P Karthigaikumar; Dr. Balavardhan Reddy; Amir Ahmed Ansari; Syed Sharik Ali; Praveen Kumar Reddy Gouni; Dr. D. Suresh; Dr. G. Brindha; Dr. Sapna Mathur; and Dr. S. Muthuselvan on May 28, 2026, for A Proactive Cyber Threat Detection System Using Behavioral Pattern Analysis.
Inventors include Dr. Ashish Kumar Tamrakar; R. Ananthakrishnan; Dr. Shailendra. Pathare; P Karthigaikumar; Dr. Balavardhan Reddy; Amir Ahmed Ansari; Syed Sharik Ali; Praveen Kumar Reddy Gouni; Dr. D. Suresh; Dr. G. Brindha; Dr. Sapna Mathur; and Dr. S. Muthuselvan.
The application for the patent was published on July 24, 2026, under issue no. 30/2026.
Abstract: The present invention relates to a proactive cyber threat detection system using behavioral pattern analysis for identifying, predicting, and mitigating cybersecurity threats in real time across interconnected digital infrastructures. The invention provides an intelligent cybersecurity framework that continuously monitors user activities, device interactions, application usage patterns, network traffic, and system events to detect suspicious behavioral deviations associated with malicious cyber activities. The system includes a data acquisition module configured to collect operational data from enterprise networks, cloud platforms, Internet of Things (IoT) devices, servers, and security monitoring systems. A behavioral profiling engine establishes dynamic behavioral baselines using machine learning and adaptive analytics techniques. An anomaly detection module compares real-time operational activities with established behavioral patterns to identify unauthorized access attempts, insider threats, malware intrusions, phishing activities, ransomware behavior, and abnormal network communication. The invention further incorporates a predictive analytics engine configured to forecast potential cyberattacks through artificial intelligence, contextual threat evaluation, and behavioral correlation analysis. A risk assessment module prioritizes detected threats based on severity and asset sensitivity, while an automated incident response framework initiates mitigation actions including access restriction, device isolation, malicious traffic blocking, and security alert generation. The system further supports integration with Security Information and Event Management (SIEM) platforms and cloud security infrastructures. The invention improves threat detection accuracy, reduces false positives, enhances cybersecurity resilience, and enables proactive protection against evolving cyber threats in modern digital environments.
Disclaimer: Curated by HT Syndication.
