MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641106990 A) filed by Mohan Babu University on September 05, 2026, for Hybrid Deep Learning System For Intelligent Iot Botnet Detection In Smart Grid Networks.
Inventors include Mr. Siva Kumar Depuru; Mr. Eskala Thakshil; Ms. Ms. Malapati Jassica; Mr. Mandhala Bharath; and Mr. M Mahendra Varma.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: The present invention relates to a Hybrid Deep Learning Framework for Intelligent IoT Botnet Detection in Smart Grid Networks configured to provide intelligent and real-time detection of malicious network activities using a hybrid deep learning architecture. The framework comprises a network traffic acquisition module, a data preprocessing module, a Convolutional Neural Network (CNN) for spatial feature extraction, a Gated Recurrent Unit (GRU) network for temporal sequence learning, a hybrid classification module, and a monitoring interface. Network traffic generated by IoT devices is continuously collected, preprocessed, and analyzed using the integrated CNN-GRU model to accurately classify benign and malicious communication. The framework automatically extracts significant network features, detects IoT botnet attacks with high accuracy, and generates real-time intrusion alerts for network administrators. The proposed invention improves cybersecurity by reducing false positive rates, enhancing detection accuracy, supporting large-scale IoT deployments, and enabling secure communication across smart grid infrastructures. The modular architecture further facilitates integration with cloud computing, edge computing, industrial IoT systems, and future artificial intelligence-based cybersecurity platforms, thereby providing a scalable, intelligent, and reliable solution for protecting next-generation IoT communication networks.
Disclaimer: Curated by HT Syndication.
