MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202641085154 A) filed by Jntuh University College Of Engineering on July 11, 2026, for An Explainable Artificial Intelligence Framework For Lightweight Malware Detection Using Compact Data Learning.
Inventors include Sabavath Raju; and Dr. K. Santhi Sree.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: The present invention discloses an Explainable Artificial Intelligence (XAI) framework for lightweight malware detection using Compact Data Learning (CDL). The framework comprises a Data Acquisition Module for collecting malware and benign samples, a Compact Data Learning Module for preprocessing, feature extraction, feature selection, feature reduction, and dimensionality reduction to generate compact feature representations, a Lightweight Malware Detection Engine for classifying malware using lightweight machine learning models, an Explainability Engine for generating feature importance and interpretable prediction explanations using SHAP, LIME, or equivalent techniques, and a Decision Support Module for confidence-based decision validation, threat score generation, and malware report preparation. The framework executes an Explainable Compact Malware Detection Algorithm (ECMDA) supported by compact feature learning and confidence threshold validation to improve malware detection efficiency while reducing computational complexity, memory utilization, and processing time. The invention is suitable for deployment in Internet of Things devices, embedded systems, edge computing platforms, mobile devices, and other resource- constrained computing environments.
Disclaimer: Curated by HT Syndication.
