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Android应用中提取的215个属性特征向量，其中包括来自Android恶意基因组（Android Malgenome）项目的1260个恶意应用，以及2539个良性应用。该数据集曾被用于开发并评估面向Android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 Transactions on Cybernetics》期刊论文《DroidFusion：一种面向Android恶意软件检测的新型多级分类器融合方法》。配套支撑文件中进一步说明了通过对Android应用进行静态代码分析得到的特征向量/属性的详细信息。