Android malware dataset for machine learning 1

Dataset consisting of feature vectors of 215 attributes extracted from 3799 applications (1260 malware apps from Android malgenome project and 2539 benign apps). The dataset has been used to develop and evaluate multilevel classifier fusion approach for Android malware detection, published in the IEEE Transactions in Cybernetics paper 'DroidFusion: A Novel Multilevel Classifier Fusion Approach for Android Malware Detection'. The supporting file contains further description of the feature vectors/attributes obtained via static code analysis of the Android apps.