Detecting and Classifying Android PUAs by Similarity of DNS queries
Mitsuhiro Hatada, Tatsuya Mori · 2017
This work develops a method of detecting and classifying “potentially unwanted applications” (PUAs) such as adware or remote monitoring tools. Our approach leverages DNS queries made by apps. Using a large sample of Android apps from third-party marketplaces, we first reveal that DNS queries can provide useful information for the detection and classification of PUAs. Next, we show that existing DNS blacklists are ineffective to perform these tasks. Finally, we demonstrate that our methodology performed with high accuracy.