The beta version of DROPS 2 is now publicly available! Check this page out at DROPS 2 now!


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/
Go back to Dagstuhl Reports

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)

pdf-format:
dagrep_v007_i007_p044_17281.pdf (2 MB)

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}
}

Keywords: big data, executable analysis, machine learning, malware, obfuscation, reverse engineering
Collection: Dagstuhl Reports, Volume 7, Issue 7
Issue Date: 2018
Date of publication: 07.02.2018

DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI