MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641062535 A) filed by Nandha Engineering College on May 18, 2026, for Machine Learning Based Network Anomaly Detection Using Advanced Learning Techniques.
Inventors include M Mahara Jothi; P Sivaganesan; and Dr R Suguna.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: ABSTRACT OF THE INVENTION The present invention relates to a machine learning-based network anomaly detection framework for identifying malicious activities, DNS tunneling attacks, zero-day intrusions, and abnormal network behavior in real-time network environments. The invention integrates supervised and tinsupervised machine learning algorithms including Random Forest, Gradient Boosting, and Isolation Forest to improve intrusion detection accuracy and detect both known and unknown cyber threats. The system collects ,DNS traffic data from network environments and performs preprocessing, normalization, and entropy-based feature engineering to extract important traffic characteristics such as query length, packet length, response size, packet timing interval, and port information. The processed feature set is analyzed using trained machine learning models to classify network traffic as normal or malicious. The invention further includes a real-time monitoring and auto-feedback mechanism capable of continuously capturing live DNS traffic and generating alerts upon detection of suspicious activities. The proposed framework provides high detection accuracy, reduced false-positive rates, and improved adaptability against evolving cyber threats. The invention is suitable for deployment in enterprise networks, cloud infrastructures, industrial systems, and modern communication environments for intelligent and scalable cybersecurity protection
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