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.

本数据集包含从3799个安卓应用中提取的215维属性特征向量，其中涵盖1260个取自Android恶意基因组（Android Malgenome Project）项目的恶意应用，以及2539个良性应用。该数据集被用于开发并评估面向安卓恶意软件检测的多级分类器融合方法，相关研究成果发表于《IEEE控制论汇刊》的论文《DroidFusion: A Novel Multilevel Classifier Fusion Approach for Android Malware Detection》。配套支持文件进一步详述了通过对安卓应用开展静态代码分析所得到的特征向量/属性的相关信息。