journal article·2021Open access

MMALE—A Methodology for Malware Analysis in Linux Environments

Jos�Javier de Vicente Mohino, Javier Bermejo Higuera, Juan Ram髇 Bermejo Higuera, Juan Antonio Sicilia Montalvo, Manuel S醤chez Rubio, Jos�Javier Mart韓ez Herraiz

Computers, Materials & Continua· Volume 67· Issue 2

Abstract

In a computer environment, an operating system is prone to malware, and even the Linux operating system is not an exception. In recent years, malware has evolved, and attackers have become more qualified compared to a few years ago. Furthermore, Linux-based systems have become more attractive to cybercriminals because of the increasing use of the Linux operating system in web servers and Internet of Things (IoT) devices. Windows is the most employed OS, so most of the research efforts have been focused on its malware protection rather than on other operating systems. As a result, hundreds of research articles, documents, and methodologies dedicated to malware analysis have been reported. However, there has not been much literature concerning Linux security and protection from malware. To address all these new challenges, it is necessary to develop a methodology that can standardize the required steps to perform the malware analysis in depth. A systematic analysis process makes the difference between good and ordinary malware analyses. Additionally, a deep malware comprehension can yield a faster and much more efficient malware eradication. In order to address all mentioned challenges, this article proposed a methodology for malware analysis in the Linux operating system, which is a traditionally overlooked field compared to the other operating systems. The proposed methodology is tested by a specific Linux malware, and the obtained test results have high effectiveness in malware detection.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Malware Detection Techniques · Network Security and Intrusion Detection · Digital and Cyber Forensics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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