Malware and Ransomware Detection Models

• URL: http://arxiv.org/abs/2207.02108v1
• Date: Tue, 5 Jul 2022 15:22:13 GMT
• Title: Malware and Ransomware Detection Models
• Authors: Benjamin Marais and Tony Quertier and St\'ephane Morucci
• Abstract summary: We introduce a novel and flexible ransomware detection model that combines two optimized models. Our detection results on a limited dataset demonstrate good accuracy and F1 scores.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Cybercrime is one of the major digital threats of this century. In particular, ransomware attacks have significantly increased, resulting in global damage costs of tens of billion dollars. In this paper, we train and test different Machine Learning and Deep Learning models for malware detection, malware classification and ransomware detection. We introduce a novel and flexible ransomware detection model that combines two optimized models. Our detection results on a limited dataset demonstrate good accuracy and F1 scores.

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