A survey on automated dynamic malware-analysis techniques and tools

Egele, Manuel; Scholte, Theodoor; Kirda, Engin; Kruegel, Christopher
ACM Computing Surveys, Volume 44, N°2, February 2012

Anti-virus vendors are confronted with a multitude of potentially malicious samples today. Receiving thousands of new samples every day is not uncommon. The signatures that detect confirmedmalicious threats are mainly still created manually, so it is important to discriminate between samples that pose a new unknown threat and those that are mere variants of known malware. This survey article provides an overview of techniques based on dynamic analysis that are used to analyze potentially malicious samples. It also covers analysis programs that employ these techniques to assist human analysts in assessing, in a timely and appropriate manner, whether a given sample deserves closer manual inspection due to its unknown malicious behavior.

Sécurité numérique
Eurecom Ref:
© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Computing Surveys, Volume 44, N°2, February 2012 http://dx.doi,org/10.1145/2089125.2089126
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