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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34P/3LR9GLB
Repositorysid.inpe.br/mtc-m21b/2016/06.07.13.54   (restricted access)
Last Update2016:06.07.13.54.45 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21b/2016/06.07.13.54.45
Metadata Last Update2021:02.04.02.20.16 (UTC) administrator
Secondary KeyINPE--PRE/
DOI10.1117/12.2223968
Citation KeyCamiloGregSant:2016:IdCoSy
TitleIdentifying compromised systems through correlation of suspicious traffic from malware behavioral analysis
Year2016
Access Date2024, May 19
Secondary TypePRE CI
Number of Files1
Size1577 KiB
2. Context
Author1 Camilo, Ana Ercilia Fernandes
2 Gregio, André
3 Santos, Rafael Duarte Coelho dos
Resume Identifier1
2
3 8JMKD3MGP5W/3C9JJ4N
Group1 CRH-CRH-INPE-MCTI-GOV-BR
2
3 LAC-CTE-INPE-MCTI-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Centro de Tencologia da Informaçaõ
3 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 ana.camilo@inpe.br
2 andre.gregio@cti.gov.br
3 rafael.santos@inpe.br
EditorTernovskiy, Igor V.
Chin, Peter
Conference NameCyber Sensing 2016
Conference LocationBaltimore, Maryland
Date17 Apr.
PublisherSPIE
Book TitleProceedings
History (UTC)2016-06-07 13:55:07 :: simone -> administrator :: 2016
2021-02-04 02:20:16 :: administrator -> simone :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
AbstractMalware detection may be accomplished through the analysis of their infection behavior. To do so, dynamic analysis systems run malware samples and extract their operating system activities and network traffic. This traffic may represent malware accessing external systems, either to steal sensitive data from victims or to fetch other malicious artifacts (configuration files, additional modules, commands). In this work, we propose the use of visualization as a tool to identify compromised systems based on correlating malware communications in the form of graphs and finding isomorphisms between them. We produced graphs from over 6 thousand distinct network traffic files captured during malware execution and analyzed the existing relationships among malware samples and IP addresses.
AreaCOMP
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Identifying compromised systems...
Arrangement 2Identifying compromised systems...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
Languageen
Target Filecamilo_identifying.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Mirror Repositoryurlib.net/www/2011/03.29.20.55
Next Higher Units8JMKD3MGPCW/3ESGTTP
8JMKD3MGPCW/3EUL8TL
Citing Item Listsid.inpe.br/bibdigital/2013/10.06.00.30 2
sid.inpe.br/mtc-m21/2012/07.13.14.58.32 1
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
NotesProceedings of the SPIE, v.9826
Empty Fieldsarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress edition format isbn issn keywords label lineage mark nextedition numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisheraddress rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url versiontype volume
7. Description control
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