MUMBAI, India, July 30 -- Intellectual Property India has published a patent application (202641087942 A) filed by Mrs. G. Sangeetha; Dr. M. Dhanasekar; Mrs. R. Rajeswari; Mrs. K. S. Hemalatha; Mr. T. S. Vinodkumar; Mrs. K. Nithyadevi; Mrs. D. Gobika; Ms. V. Manjula; Ms. K. Kavipriya; Ms. M. Priyadharshini; and Mr. S. Abivijay on July 18, 2026, for Machine Learning Driven Cyberthreat Detection And Response Automation System For Enterprise Network Security.
Inventors include Mrs. G. Sangeetha; Dr. M. Dhanasekar; Mrs. R. Rajeswari; Mrs. K. S. Hemalatha; Mr. T. S. Vinodkumar; Mrs. K. Nithyadevi; Mrs. D. Gobika; Ms. V. Manjula; Ms. K. Kavipriya; Ms. M. Priyadharshini; and Mr. S. Abivijay.
The application for the patent was published on July 24, 2026, under issue no. 30/2026.
Abstract: The present invention discloses a machine learning driven cyber threat detection and response automation system for enterprise network security that intelligently detects, analyzes, classifies, and mitigates cybersecurity threats across enterprise infrastructures. The system integrates network data acquisition, behavioral analytics, machine learning based threat detection, threat intelligence correlation, adaptive learning mechanisms, and automated incident response capabilities to provide real-time cybersecurity protection. By continuously monitoring enterprise network activities and identifying anomalous behaviors, the system is capable of detecting both known and emerging cyber threats with enhanced accuracy. Upon threat identification, automated remediation actions are executed to contain and mitigate security incidents. The adaptive learning framework continuously improves detection performance using historical incident data and threat intelligence, thereby enhancing enterprise security resilience, minimizing response times, and reducing manual cybersecurity management efforts across cloud, on-premises, and hybrid network environments.
Disclaimer: Curated by HT Syndication.
