While financial related malware is on the rise, the definition of such is still ambiguous, specifically for malware targeting Android devices. In order to reliably defend against Android-targeting financial malware, a classification is required.
This article proposes a taxonomy model based on malware samples representing 32 families. The evaluation and characterization of this model aims to open the possibility of an automatic malware categorization. This helps analysts to defend against financial related malware more effectively.