DiOS: Dynamic Privacy Analysis of iOS Applications

dc.contributor.authorKurtz, Andreas
dc.contributor.authorWeinlein, Andreas
dc.contributor.authorSettgast, Christoph
dc.contributor.authorFreiling, Felix
dc.date.accessioned2014-06-10
dc.date.available2023-10-17T07:45:34Z
dc.date.created2014
dc.date.issued2014-06-10
dc.description.abstractWe present DiOS, a practical system to perform automated dynamic privacy analysis of iOS apps. DiOS provides a highly scalable and fully automated solution to schedule apps from the official Apple App Store for privacy analysis to iOS devices. While apps are automatically executed, user interaction is simulated using random and smart execution strategies, and sensitive API calls as well as network connections are tracked. We evaluated the system on 1,136 of the most popular free apps from the iOS App Store and found out that almost 20% of all investigated apps are tracking users' locations on every app start, one third of all accesses to users' address books are attributed to apps from the social network category and almost half of all apps are tracking users' app usage behavior by incorporating tracking and advertising libraries.en
dc.identifier.opus-id4755
dc.identifier.urihttps://open.fau.de/handle/openfau/4755
dc.identifier.urnurn:nbn:de:bvb:29-opus4-47559
dc.language.isoen
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/de/deed.de
dc.subject.ddcDDC Classification::0 Informatik, Informationswissenschaft, allgemeine Werke :: 00 Informatik, Wissen, Systeme :: 004 Datenverarbeitung; Informatik
dc.titleDiOS: Dynamic Privacy Analysis of iOS Applicationsen
dc.typereport
dcterms.publisherFriedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
local.sendToDnbfree*
local.series.id9
local.series.nameTechnical reports / Department Informatik
local.series.numberCS-2014-03
local.subject.fakultaetTechnische Fakultät / Department Informatik
local.subject.gndApps
local.subject.gndiOS
local.subject.gndPrivatsphäre
local.subject.gndDynamische Analyse
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