Authors:
Gerald Palfinger
1
;
2
Affiliations:
1
A-SIT Secure Information Technology Center Austria, Seidlgasse 22 / Top 9, 1030 Vienna, Austria
;
2
Institute of Applied Information Processing and Communications (IAIK), Graz University of Technology, Inffeldgasse 16a, 8010 Graz, Austria
Keyword(s):
Fingerprinting, Smartphones, Apple iOS, Automatic Detection.
Abstract:
Tracking has allowed application providers to offer the vast majority of their applications for free as it allows them to target advertising. However, tracking has proven to be an invasion of user privacy. To counter this, operating system vendors have removed access to unique identifiers in their APIs. Nevertheless, applications can still combine other non-unique data from the device to create a unique fingerprint. Until now, it has not been well understood what kind of information is available to do so on iOS. This paper addresses this gap by introducing the OCScraper framework, a tool for automatically discovering fingerprintable information sources on iOS devices. OCScraper does this by systematically crawling the API of the operating system. In the process, it creates objects on which methods are called and properties are queried. In our evaluation, we show that OCScraper can successfully invoke a large number of methods and retrieve the majority of parameters. We discover hundr
eds of robust information sources that provide distinct bits of information which can be used to create a cross-application fingerprint.
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