Authors: Research Scholar Mr. Narender Kumar, Associate Professor Dr. Pramod Kumar
Abstract: The primary objective of this research is to develop and evaluate an effective machine learning-based framework for the early detection of ransomware attacks. The study investigates a range of machine learning techniques, including supervised classification, anomaly detection, and clustering methods, to distinguish ransomware activities from legitimate system behavior. It focuses on extracting and analyzing critical behavioral features such as file access patterns, process execution characteristics, and network communication activities to train predictive models capable of achieving high detection accuracy while minimizing false positive rates.
