YuiIroha/McNdroid

McNdroid是一个大规模、纵向、多模态的Android恶意软件检测数据集，旨在基准概念漂移鲁棒性。它涵盖从2013年到2025年收集的样本，并提供三种互补的模态：静态特征向量、API调用图（GML）和基于JSON的行为表示。数据集还包括丰富的元数据CSV和每个供应商家族级别的判定，支持细粒度标签分析和多标签学习。数据集总结：模态包括静态特征（NPZ）、API调用图（GML）、JSON行为特征；时间跨度为2013年至2025年；总大小约10.9 GB；按年份划分训练/测试集，并采用时间评估协议；标签包括二进制（恶意软件/良性）和多供应商家族级别判定。McNdroid is a large-scale, longitudinal, multi-modal Android malware detection dataset designed to benchmark concept drift robustness. It covers samples collected from 2013 to 2025, and provides three complementary modalities: static feature vectors, API call graphs (GML), and JSON-based behavioral representations. The dataset also includes rich metadata in CSV format and vendor family-level annotations, supporting fine-grained label analysis and multi-label learning. Dataset Summary: The modalities include static features (NPZ), API call graphs (GML), and JSON behavioral features; the time span ranges from 2013 to 2025; the total size is approximately 10.9 GB; the training/test splits are stratified by year, adopting a temporal evaluation protocol; the labels include binary (malware/benign) and multi-vendor family-level annotations.