MUMBAI, India, Feb. 6 -- Intellectual Property India has published a patent application (202541085127 A) filed by Mrs. M. Sravani; and Dr. R. Vijaya Prakash, Warangal, Telangana, on Sept. 8, 2025, for 'hybrid ensemble-based system and method for intelligent malware detection using machine and deep learning classifiers.'
Inventor(s) include Mrs. M. Sravani; and Dr. R. Vijaya Prakash.
The application for the patent was published on Feb. 6, under issue no. 06/2026.
According to the abstract released by the Intellectual Property India: "The present invention discloses a hybrid ensemble learning framework for detecting malware using a combination of traditional machine learning and deep learning models. The system extracts static and dynamic features from software artifacts and processes them using a set of diverse base classifiers, including models such as Support Vector Machines, Random Forests, Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) networks. A stacking-based ensemble aggregation strategy is employed, where the outputs of base classifiers are input into a meta-classifier to improve prediction accuracy. The framework supports periodic retraining using new threat data to adapt to emerging malware variants, including zero-day threats. This invention enhances malware detection accuracy, reduces false positives, and improves resilience against obfuscation techniques. The proposed system is applicable to desktop, mobile, and cloud environments, providing a scalable and intelligent solution for real-time malware classification and cybersecurity defense."
Disclaimer: Curated by HT Syndication.
