License: 
Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.7.7.44
URN: urn:nbn:de:0030-drops-84222
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/8422/
Zennou, Sarah ;
Debray, Saumya K. ;
Dullien, Thomas ;
Lakhothia, Arun
Weitere Beteiligte (Hrsg. etc.): Sarah Zennou and Saumya K. Debray and Thomas Dullien and Arun Lakhotia
Malware Analysis: From Large-Scale Data Triage to Targeted Attack Recognition (Dagstuhl Seminar 17281)
Abstract
This report summarizes the program and the outcomes of the Dagstuhl Seminar 17281, entitled "Malware Analysis: From Large-Scale Data Triage to Targeted Attack Recognition". The seminar brought together practitioners and researchers from industry and academia to discuss the state-of-the art in the analysis of malware from both a big data perspective and a fine grained analysis. Obfuscation was also considered. The meeting created new links within this very diverse community.
BibTeX - Entry
@Article{zennou_et_al:DR:2018:8422,
author = {Sarah Zennou and Saumya K. Debray and Thomas Dullien and Arun Lakhothia},
title = {{Malware Analysis: From Large-Scale Data Triage to Targeted Attack Recognition (Dagstuhl Seminar 17281)}},
pages = {44--53},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2018},
volume = {7},
number = {7},
editor = {Sarah Zennou and Saumya K. Debray and Thomas Dullien and Arun Lakhotia},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2018/8422},
URN = {urn:nbn:de:0030-drops-84222},
doi = {10.4230/DagRep.7.7.44},
annote = {Keywords: big data, executable analysis, machine learning, malware, obfuscation, reverse engineering}
}
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Keywords: |
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big data, executable analysis, machine learning, malware, obfuscation, reverse engineering |
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Collection: |
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Dagstuhl Reports, Volume 7, Issue 7 |
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Issue Date: |
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2018 |
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Date of publication: |
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07.02.2018 |
