Intellectual Property India Publishes Patent Application for "network-Based Intrusion Detection And Drone-Based Weapon Detection Using A Cnn Algorithm"

MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202541005914 A) filed by Dr S. Brindha on January 24, 2025, for "network-Based Intrusion Detection And Drone-Based Weapon Detection Using A Cnn Algorithm".

Inventors include Dr S. Brindha; K. Sudha; T. P. Kamatchi; A. Dhamayanthi; A. Amish Peniel; V. Harishraj; K. S. Harishsiva; A. Hassan; R. Namith Kumar; Niranjan Kumar; Manjunathan; G. Parthive; A. Pranith; M. Praveen; Tamizh Eniyan; and Saravanan.

The application for the patent was published on July 31, 2026, under issue no. 31/2026.

Abstract: ABSTRACT OF THE INVENTION NETWORK-BASED INTRUSION DETECTION AND DRONE-BASED WEAPON DETECTION USING A CNN ALGORITHM Ensuring security is a paramount concern, encompassing both digital and physical domains. This project focuses on developing an integrated system that combines network-based 10 intrusion detection and drone-based weapon detection using convolutional neural networks (CNNS). The proposed system addresses two critical challenges: detecting unauthorized access and malicious activities within a computer network and identifying weapons m restricted zones using drones equipped with real-time image processing capabilities. The network intrusion detection system (NIDS) analyzes network traffic to identify abnormal 15 patterns, such as unauthorized access or malicious activities. By leveraging CNNs for feature extraction and classification, the system can accurately distinguish between benign and malicious traffic, enhancing cybersecurity measures. 20 25 The drone-based weapon detection system utilizes a drone-mounted camera to identify weapons in real-time. A CNN-based object detection model processes live video streams to detect and classify weapons with high accuracy, triggering alerts to ensure rapid response in potential threat scenarios. The integration of these two subsystems into a centralized monitoring framework ensures a comprehensive security solution that spans both cyberspace and physical environments. The project emphasizes real-time processing, accuracy, and scalability, contributing significantly to the fields of artificial intelligence, cybersecurity, and surveillance. This innovative system has applications in diverse areas, including critical infrastructure protection, public safety, and military operations, demonstrating its potential to address modern security challenges effectively.

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