CRAIJul 5, 2022

AI-based Malware and Ransomware Detection Models

arXiv:2207.02108v216 citationsh-index: 6
Originality Synthesis-oriented
AI Analysis

This work addresses cybersecurity threats for organizations and individuals, but it appears incremental as it builds on existing models with some enhancements.

The paper tackled the problem of detecting malware and ransomware by training and testing various machine learning and deep learning models, introducing a combined solution that showed improvements in detection performance and flexibility.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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