McNdroid tiny for NeurIPS: A Longitudinal Multimodal Benchmark for Robust Drift Detection in Android Malware
收藏DataCite Commons2026-05-02 更新2026-05-07 收录
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https://zenodo.org/doi/10.5281/zenodo.19984827
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资源简介：
McNdroid is a large-scale, longitudinal, multimodal Android malware detection dataset designed to benchmark concept drift robustness. It spans 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 a rich metadata CSV and per-vendor family-level verdicts, supporting fine-grained label analysis and multi-label learning.
提供机构：
Zenodo
创建时间：
2026-05-02
