MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202641008989 A) filed by Vemu Institute Of Technology, Chittoor, Andhra Pradesh, on Jan. 29, for 'anomaly detection framework for identifying insider threats.'
Inventor(s) include Mr. V. Sreedhar; Ms. G. Nagaveni; and Mr. Ramesh Peramalasetty.
The application for the patent was published on Feb. 13, under issue no. 07/2026.
According to the abstract released by the Intellectual Property India: "The current invention reveals a behavior-driven anomaly detection system for detecting insider threats in organizational networks through advanced machine learning and behavioral analysis. The invention monitors user activity data and network logs to build behavioral baselines and detect anomalies that signal insider abuse. By using algorithms like Random Forest, Naive Bayes, Logistic Regression, Gradient Boosting, and Support Vector Machine, the system classifies anomalous behaviors in real-time with high precision and low false positives. Anomalies are given contextual risk scores according to role, time, and sensitivity of data, prioritizing response to high-risk events. The system is integrated into current enterprise security infrastructures and uses adaptive learning for ongoing improvement. Its privacy-preserving, scalable, and modular architecture reinforces organizational resilience against dynamic insider threats in a manner that supports data protection compliance. The invention offers a proactive, adaptive, and efficient means of protecting mission-critical digital environments from insider security threats."
Disclaimer: Curated by HT Syndication.
