MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541123220 A) filed by Vellore Institute Of Technology, Vellore, Tamil Nadu, on Dec. 6, 2025, for 'hybrid machine learning system for network intrusion detection.'
Inventor(s) include Dr. Gunasekar M; Mr. Wahhaj Mustafa; Mr. Saad Mohammed Mazhar Khan; and Ms. Sarah Ahmad.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "The present disclosure provides a hybrid machine learning system for network intrusion detection. The system includes a data preprocessing module configured to receive network traffic data and perform data preparation operations including missing value imputation, duplicate removal, and feature scaling. A feature engineering module addresses class imbalance using synthetic minority oversampling. A classical ensemble learning module includes multiple base classifiers combined using ensemble techniques. A deep learning module includes a Convolutional Neural Network (CNN) for spatial feature extraction and a Long Short-Term Memory (LSTM) network for temporal sequence modeling. A hybrid architecture combines the classical ensemble learning module with the deep learning module. An evaluation module assesses model performance using classification metrics. The system processes network flow sequences through convolutional layers for spatial pattern detection followed by recurrent layers for temporal dependency analysis, enabling detection of sophisticated attack patterns."
Disclaimer: Curated by HT Syndication.
