Lightweight, Effective Detection and Characterization of Mobile Malware Families

DroidMalVet DroidMalVet dataset provides a curated collection of 20 code-level metrics extracted from Android malware applications, each labeled with its corresponding malware family. It comprises 24,252 malicious apps categorized into 202 malware families. The metrics capture structural and behavioral properties of the malicious apps and are grouped into four categories: complexity, dimensional, object-oriented, and Android-oriented metrics. These metrics were extracted by decompiling each malicious application into Smali code and analyzing it with a modified static analysis tool. This dataset enables researchers to study malware family detection, characterization, and evolution with a compact and efficient feature set. Further details can be found in our paper “Lightweight, Effective Detection and Characterization of Mobile Malware Families” [PDF], IEEE Transactions on Computers, 2022. If your papers or articles used our dataset, please include a citation to our paper: @ARTICLE {DroidMalVet, author={Elish, Karim and Elish, Mahmoud and Almohri, Hussain}, journal={IEEE Transactions on Computers}, title={Lightweight, Effective Detection and Characterization of Mobile Malware Families}, year={2022}, volume={71}, number={11}, pages={2982-2995}}