Ecole d'ingénieur et centre de recherche en Sciences du numérique

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.

Document Doi Bibtex

Titre:A survey on automated dynamic malware-analysis techniques and tools
Mots Clés:Security, Dynamic analysis, malware
Type:Journal
Langue:English
Ville:
Date:
Département:Sécurité numérique
Eurecom ref:3674
Copyright: © 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
Bibtex: @article{EURECOM+3674, doi = {http://dx.doi,org/10.1145/2089125.2089126}, year = {2012}, month = {02}, title = {{A} survey on automated dynamic malware-analysis techniques and tools}, author = {{E}gele, {M}anuel and {S}cholte, {T}heodoor and {K}irda, {E}ngin and {K}ruegel, {C}hristopher}, journal = {{ACM} {C}omputing {S}urveys, {V}olume 44, {N}°2, {F}ebruary 2012 }, url = {http://www.eurecom.fr/publication/3674} }
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