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Machine Learning for Ransomware Detection by 201sc004 is a document available to read on EtoBox.

What is Machine Learning for Ransomware Detection about?

The document discusses the increasing threat of ransomware attacks and the application of machine learning (ML) techniques for detection. It details the development of a robust ML model that achieved 97.85% accuracy with a 2% false positive rate using a dataset of 1165 samples, including both benign and ransomware examples. The methodology involved data collection, preprocessing, feature extraction, and the application of various ML classifiers to enhance ransomware detection capabilities.

Author

201sc004

Language

EN