Malware: the never-ending arm race

Article


Menendez Benito, H. 2021. Malware: the never-ending arm race. Open Journal of Cybersecurity. 1 (1), pp. 1-25. https://doi.org/10.46723/ojc.1.1.3
TypeArticle
TitleMalware: the never-ending arm race
AuthorsMenendez Benito, H.
Abstract

"Antivirus is death"' and probably every detection system that focuses on a single strategy for indicators of compromise. This famous quote that Brian Dye --Symantec's senior vice president-- stated in 2014 is the best representation of the current situation with malware detection and mitigation. Concealment strategies evolved significantly during the last years, not just like the classical ones based on polimorphic and metamorphic methodologies, which killed the signature-based detection that antiviruses use, but also the capabilities to fileless malware, i.e. malware only resident in volatile memory that makes every disk analysis senseless. This review provides a historical background of different concealment strategies introduced to protect malicious --and not necessarily malicious-- software from different detection or analysis techniques. It will cover binary, static and dynamic analysis, and also new strategies based on machine learning from both perspectives, the attackers and the defenders.

KeywordsGeneral Medicine, Biochemistry, Biochemistry, Sociology and Political Science, History, History, Cultural Studies, Literature and Literary Theory, Visual Arts and Performing Arts, History, History, Political Science and International Relations, Sociology and Political Science, Sociology and Political Science, History, Anthropology, Cultural Studies, Literature and Literary Theory, Linguistics and Language, History, Language and Linguistics, Cultural Studies
PublisherEndless Science Ltd
JournalOpen Journal of Cybersecurity
Publication dates
Print08 Sep 2021
Publication process dates
Deposited16 Sep 2021
Output statusPublished
Publisher's version
License
Copyright Statement

This work is licensed under a Creative Commons “AttributionNonCommercial-ShareAlike 4.0 International” license.

Digital Object Identifier (DOI)https://doi.org/10.46723/ojc.1.1.3
LanguageEnglish
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