AI-based Malware and Ransomware Detection Models

Benjamin Marais, Tony Quertier, Stéphane Morucci
7/5/2022
cs.CRcs.AI

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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 solution that combines two optimized models for malware and ransomware detection. Our results demonstrate some improvements both in terms of detection performances and flexibility. In particular, our combined models pave the way for easier future enhancements using specialized and thus interchangeable detection modules.

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Cite this paper

@article{marais2022aibased,
  title  = {AI-based Malware and Ransomware Detection Models},
  author = {Benjamin Marais and Tony Quertier and Stéphane Morucci},
  year   = {2022},
  eprint = {2207.02108},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2207.02108v2}
}

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