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AI-based Malware and Ransomware Detection Models
Benjamin Marais, Tony Quertier, Stéphane Morucci

AI-based Malware and Ransomware Detection Models

Science & Mathematics Published 2022 Verification Pending

Overview & Synopsis

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.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title AI-based Malware and Ransomware Detection Models
Author / Organization Benjamin Marais, Tony Quertier, Stéphane Morucci
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2022
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-247312
Original Source Link Visit Source Page on hal.science »