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Malware Detection with AI

Khalil Moriello,Hugo Scolnik

2024 · DOI: 10.1109/ARGENCON62399.2024.10735932
IEEE Biennial Congress of Argentina · 0 Citations

TLDR

The aim is to offer the reader a concise introduction to the different techniques and algorithmic formulations used in the dynamic analysis of malware, focusing on several machine learning techniques used in this context, though without providing experimental results.

Abstract

In this paper, we will present two existing approaches that utilize machine learning techniques for dynamic analysis, as well as an approach that employs deep learning. Additionally, we will propose an enhancement to a previously studied method. For the dynamic analysis of malware, we review various current research directions, focusing on several machine learning techniques used in this context, though without providing experimental results. The aim is to offer the reader a concise introduction to the different techniques and algorithmic formulations. Similarly, the approach involving deep learning will be discussed. Finally, we introduce a modification to an idea previously proposed in the literature and analyze the differences it brings.

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