MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641078486 A) filed by Mlr Institute Of Technology on June 25, 2026, for Real-Time Network Anomaly Detection System.
Inventor includes Mr. G. V Rambabu.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: The present invention relates to a machine learning-based system for real-time anomaly detection in network security environments. The invention integrates convolutional neural networks, long short-term memory networks, attention mechanisms, federated learning, adaptive thresholding, and explainable artificial intelligence techniques to provide accurate and interpretable detection of anomalous network activities. Network traffic data collected from enterprise, cloud, edge, and Internet of Things environments are preprocessed and analyzed using a hybrid deep learning architecture capable of identifying both known and previously unseen cyber threats. A federated learning framework enables collaborative model training while preserving privacy by preventing the transfer of raw traffic data between participating nodes. Adaptive thresholding dynamically adjusts detection sensitivity according to changing network conditions, thereby reducing false-positive alerts. SHAP-based explain ability mechanisms provide feature-level interpretation of anomaly detection decisions, enhancing analyst confidence and operational transparency. Continual learning capabilities allow adaptation to emerging cyber threats and zero-day attacks. The proposed system achieves high detection accuracy, low latency, scalability, and privacy preservation, making it suitable for deployment across heterogeneous network infrastructures requiring real- time cybersecurity protection.
Disclaimer: Curated by HT Syndication.
