AndroPRINT

Autor: Gerald Palfinger, Bernd Prünster
Rok vydání: 2020
Předmět:
Zdroj: ARES
DOI: 10.1145/3407023.3407055
Popis: In recent Android versions, access to various (unique) identifiers has been restricted or completely removed for third-party applications. However, many information sources can still be combined to create a fingerprint, effectively substituting the need for these unique identifiers. Until now, finding these fingerprintable sources required manually sifting through the API documentation to identify each information source individually. This paper presents AndroPRINT, a framework that automatically recognizes fingerprintable information sources on Android devices. For this purpose it automatically invokes methods, queries fields, and retrieves data from content providers. We show that this framework allows automating the elaborate task of finding such fingerprintable information sources in different experiments. In these experiments, a variety of information sources could be identified, which provide a vast amount of unique features for fingerprinting. Furthermore, AndroPRINT detected undocumented unique device identification features, which are a result of manufacturer adaptations. These vendor customisations even revealed personal data, such as the user's email address and cryptographic keys used for cross-device communication. The fact that this information can be retrieved without the user noticing means that vendor customisations can effectively defeat the tight permission system of modern smartphone operating systems.
Databáze: OpenAIRE