March 30, 2023

SpywareNews.com

Dedicated Forum to help removing adware, malware, spyware, ransomware, trojans, viruses and more!

Mixed Signals: Analyzing Software Attribution Challenges in the Android Ecosystem. (arXiv:2211.13104v1 [cs.CR])

The ability to identify the author responsible for a given software object is
critical for many research studies and for enhancing software transparency and
accountability. However, as opposed to other application markets like iOS,
attribution in the Android ecosystem is known to be hard. Prior research has
leveraged market metadata and signing certificates to identify software authors
without questioning the validity and accuracy of these attribution signals.
However, Android app authors can, either intentionally or by mistake, hide
their true identity due to: (1) the lack of policy enforcement by markets to
ensure the accuracy and correctness of the information disclosed by developers
in their market profiles during the app release process, and (2) the use of
self-signed certificates for signing apps instead of certificates issued by
trusted CAs.

In this paper, we perform the first empirical analysis of the availability,
volatility and overall aptness of publicly available metadata for author
attribution in Android app markets. To that end, we analyze a dataset of over
2.5 million market entries and apps extracted from five Android markets for
over two years. Our results show that widely used attribution signals are often
missing from market profiles and that they change over time. We also invalidate
the general belief about the validity of signing certificates for author
attribution. For instance, we find that apps from different authors share
signing certificates due to the proliferation of app building frameworks and
software factories. Finally, we introduce the concept of attribution graph and
we apply it to evaluate the validity of existing attribution signals on the
Google Play Store. Our results confirm that the lack of control over publicly
available signals can confuse the attribution process.