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Malicious attacks, malware, and ransomware families pose critical security issues to cybersecurity, and it may cause catastrophic damages to computer systems, data centers, web, and mobile applications across various industries and businesses. Traditional anti-ransomware systems struggle to fight against newly created sophisticated attacks. Therefore, state-of-the-art techniques including Machine Learning (ML) algorithms can be immensely utilized in the development of innovative ransomware solutions. In this module, we apply Logistic Regression (LR), a Machine Learning algorithm to classify ransomware using a real-world ransomware dataset to evaluate our proposed framework. In addition, we investigate important features towards the ransomware classification using LR.

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