Towards detecting device fingerprinting on iOS with API function hooking

被引:1
|
作者
Heid, Kris [1 ]
Andrae, Vincent [1 ]
Heider, Jens [1 ]
机构
[1] Fraunhofer SIT ATHENE, Natl Res Ctr Appl Cybersecur, Darmstadt, Germany
来源
PROCEEDINGS OF THE 2023 EUROPEAN INTERDISCIPLINARY CYBERSECURITY CONFERENCE, EICC 2023 | 2023年
关键词
iOS; privacy; fingerprinting; static analysis; dynamic analysis;
D O I
10.1145/3590777.3590790
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Device fingerprinting is a technique that got popular at the end of the 90s by websites, to identify and track users. One of the biggest drivers behind such practices are advertising companies to identify users interests to personalize ads. From a user's perspective, this, of course, raises privacy concerns. While device fingerprinting and its detection has been extensively studied in the context of web browsing, little research has been conducted on device fingerprinting in mobile apps and especially iOS apps. In this paper, we capture the current state of device fingerprinting in iOS apps, and explore possible approaches for fingerprinting detection on mobile devices using static and dynamic app analysis techniques. Finally, we present a first heuristic approach for automatic behavior-based fingerprinting detection on iOS only using spatial and temporal context of relevant API-calls.
引用
收藏
页码:78 / 84
页数:7
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