MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202611062514 A) filed by Ajay Kumar Garg Engineering College on May 18, 2026, for Ai-Based Real-Time Network Intrusion Detection System Using Cnn-Lstm And Ensemble Learning And Working Method Thereof.
Inventors include Archit Tiwari; Asmit Yadav; Ayush Agrawal; Devansh Agrawal; Ms. Mahima Saxena; and Ms. Ritika Dhyani.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: The present invention discloses an artificial intelligence-based real-time network intrusion detection system (100) and working method thereof. The system comprises a packet capture engine (102) configured to acquire live network traffic, a flow construction module (104) for generating bidirectional flow records, and a feature extraction and preprocessing module (106) for deriving structured traffic features. A hybrid deep learning detection engine (108), including a convolutional neural network and long short- term memory network, extracts spatial and temporal patterns, respectively. An ensemble decision module (110) refines classification outputs using gradient boosting. A real-time inference pipeline (114) enables low-latency processing, while a monitoring and alert management module (116) generates real-time alerts and visualizations. The system facilitates accurate detection of known and unknown cyber threats with reduced false positives, thereby enhancing network security across scalable deployment environments. Accompanied Drawings [Fig. 1-4]
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