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    MMALE a methodology for malware analysis in linux environments

    Autor: 
    de Vicente Mohino, José Javier (1)
    ;
    Bermejo-Higuera, Javier
    ;
    Bermejo Higuera, Juan Ramón
    ;
    Sicilia, Juan Antonio (1)
    ;
    Sánchez Rubio, Manuel (1)
    ;
    Martínez Herraiz, José-Javier
    Fecha: 
    2021
    Palabra clave: 
    malware analysis; methodology analysis; linux malware; IoT malware; Scopus; WOS(2)
    Tipo de Ítem: 
    Articulo Revista Indexada
    URI: 
    https://reunir.unir.net/handle/123456789/11516
    DOI: 
    https://doi.org/10.32604/cmc.2021.014596
    Dirección web: 
    https://www.techscience.com/cmc/v67n2/41332
    Open Access
    Resumen:
    In a computer environment, an operating systemis prone to malware, and even the Linux operating system is not an exception. In recent years, malware has evolved, and attackers have becomemore qualified compared to a fewyears 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, somost of the research efforts have been focused on itsmalware 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.
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