MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202641109618 A) filed by Anjana P Suresh; Anusri R; Dhanyalakshmi K M; Lokshana N; Vivekanandha College Of Engineering For Women; and Mrs. K. Soniya Lakshmi on September 12, 2026, for A System And Method For Deep Learning-Based Network Malware Detection With Iot Monitoring.
Inventors include Anjana P Suresh; Anusri R; Dhanyalakshmi K M; Lokshana N; Vivekanandha College Of Engineering For Women; and Mrs. K. Soniya Lakshmi.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: The invention relates to cybersecurity, particularly real-time network malware detection using deep learning with IoT-assisted monitoring. A system acquires live network traffic or dataset-derived flow data, preprocesses the data by cleaning, encoding and normalizing records, extracts traffic features including flow duration, packet counts, packet lengths, rates, protocol and port information, and applies a trained ANN/DNN detection engine to classify traffic as normal or malicious based on a prediction threshold. An ESP32-based monitoring unit with Wi-Fi acquires network parameters and supports remote observation, local OLED display, and hardware alerts through LED and buzzer. Detection outputs are presented on an interactive dashboard, while automated alerts, including administrator notifications, are generated for malicious events. Event data, confidence scores, classifications and logs are securely stored for historical analytics, auditing and reporting. The integrated architecture improves detection of unknown and evolving attacks over signature-based systems. Fig. 1 best characterises the invention.
Disclaimer: Curated by HT Syndication.
