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dc.contributor.authorZurutuza, Urko
dc.contributor.otherSomarriba Jarquin, Oscar Manuel
dc.date.accessioned2023-01-09T15:18:30Z
dc.date.available2023-01-09T15:18:30Z
dc.date.issued2018
dc.identifier.isbn9781538635094en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=154545en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/5932
dc.description.abstractNowadays, with the predominance of smart devices such as smartphones, mobile malware attacks have increasingly proliferated. There is an urgent need of detecting potential malicious behaviors so as to hinder them. Furthermore, Android malware is one of the major security issues and fast growing threats facing the Internet in the mobile arena. At the same time, DNS (Domain Name System) is widely misused by miscreants in order to provide Internet connection within malicious networks. Here, we propose an infrastructure for monitoring the Android applications in a platform-independent manner, introducing hooks in order to trace restricted API calls used at runtime of the application. These traces are collected at a central server were the application behavior filtering, string matching, and visualization takes place. From these traces we can extract malicious URLs and correlate them with DNS service network traffic, enabling us to find presence of malware running at the network level.en
dc.language.isoengen
dc.publisherIEEEen
dc.rights© 2018 IEEEen
dc.subjectAndroid malwareen
dc.subjectAPI callsen
dc.subjectDynamic behavior analysisen
dc.subjectDNS queriesen
dc.subjectCollaborative frameworken
dc.titleA collaborative framework for android malware detection using DNS & dynamic analysisen
dcterms.accessRightshttp://purl.org/coar/access_right/c_abf2en
dcterms.sourceIEEE 37th Central America and Panama Convention (CONCAPAN XXXVII)en
local.contributor.groupAnálisis de datos y ciberseguridades
local.description.peerreviewedtrueen
local.identifier.doihttps://doi.org/10.1109/CONCAPAN.2017.8278529en
local.contributor.otherinstitutionhttps://ror.org/00brc6r59es
local.source.detailsManagua, 15-17 November 2017. IEEE, 2018en
oaire.format.mimetypeapplication/pdf
oaire.file$DSPACE\assetstore
oaire.resourceTypehttp://purl.org/coar/resource_type/c_c94fen
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aaen


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