MUMBAI, India, Oct. 12 -- Intellectual Property India has published a patent application (202641119649 A) filed by Anurag University on October 06, 2026, for An Ensemble Machine Learning-Based Intelligent System And Method For Real-Time Network Traffic Anomaly Detection.
Inventors include Dr. Jothikumar R; Mr. Boopathi S; Mrs. J Maria Shanthi; Mr. J Venkat Ramana; Mr. Jayendra Kumar; Dr. Deva Rajashekar; and Dr. V Vinay Kumar.
The application for the patent was published on October 09, 2026, under issue no. 41/2026.
Abstract: The present system discloses an ensemble machine learning-based intelligent system and method for real-time network traffic anomaly detection. The system comprises a network traffic acquisition module, preprocessing module, feature extraction and selection module, ensemble machine learning module, anomaly scoring module, real-time decision engine, alert generation module, monitoring module, and model updating module. Network traffic is continuously acquired and transformed into feature vectors representing traffic, protocol, temporal, and behavioral characteristics. Multiple machine learning models, including Random Forest, Support Vector Machine, Decision Tree, Logistic Regression, Gradient Boosting, and Isolation Forest, independently analyze the feature vectors. The resulting predictions are combined using an ensemble mechanism such as weighted voting or probability aggregation to generate an ensemble anomaly score. The anomaly score is compared with a configurable threshold to identify normal and anomalous traffic and classify detected anomalies into corresponding attack categories. The system further provides real-time alerts and feedback-based model updating, thereby enabling continuous and adaptive network traffic anomaly detection for enterprise, cloud, IoT, industrial, and other network environments.
Disclaimer: Curated by HT Syndication.
