ArticleScientific data2025
MH-1M: A 1.34 Million-Sample Multi-Feature Android Malware Dataset with Rich Metadata.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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Who cites it
1 citing paper in PubMed.
- MH-1M: A 1.34 Million-Sample Multi-Feature Android Malware Dataset with Rich Metadata.Scientific data · 2025Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present MH-1M, one up-to-date dataset for advanced Android malware research. The dataset comprises 1,340,515 applications, encompassing a wide range of features and extensive metadata. To ensure accurate malware classification, we employ the VirusTotal API, integrating multiple detection engines for comprehensive and reliable assessment. Our Figshare, Harvard Dataverse and GitHub repositories provide open access to the processed dataset and its extensive supplementary metadata, totaling more than 400 GB of data and including the outputs of the feature extraction pipeline as well as the corresponding VirusTotal reports. Our findings underscore the MH-1M dataset's role in understanding the evolving landscape of malware.
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Registered trials
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