Title: Methods for automatic malware analysis and classification: a survey

Authors: Toni Gržinić; Eduardo Blázquez González

Addresses: Reversing Labs, Radnicka Cesta 37A, Zagreb, Croatia ' Universidad Carlos III de Madrid, Av. de la Universidad, 30,28911 Leganés, Madrid, Spain

Abstract: In this survey, we try to summarise modern malware classification methods and analysis tools, and give an insight into the current research efforts that are used to build state-of-the-art malware classification systems that are used to detect the most dangerous malware families built for the operating system, Microsoft Windows. Before diving into automatic classification methods and features (malware indicators) used, we describe the accompanying analysis approaches that are the fundamental building block of every automatic classifier. This paper has the intention to summarise and categorise various efforts of researches that emerged in the last years and recognise upcoming challenges in the vibrant malware landscape.

Keywords: malware classification; static analysis; dynamic analysis; survey.

DOI: 10.1504/IJICS.2022.121297

International Journal of Information and Computer Security, 2022 Vol.17 No.1/2, pp.179 - 203

Received: 17 Aug 2019
Accepted: 20 Apr 2020
Published online: 04 Mar 2022 *

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