Android malware dataset for machine learning 2

Dataset consisting of feature vectors of 215 attributes extracted from 15,036 applications (5,560 malware apps from Drebin project and 9,476 benign apps). The dataset has been used to develop and evaluate multilevel classifier fusion approach for Android malware detection, published in the IEEE Transactions on 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15036个安卓应用中提取的215个属性的特征向量，其中涵盖来自Drebin项目的恶意应用5560个、良性应用9476个。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 Transactions on Cybernetics》期刊的论文《DroidFusion: A Novel Multilevel Classifier Fusion Approach for Android Malware Detection》。配套支持文件中对通过静态代码分析安卓应用得到的特征向量与属性进行了进一步阐释。