MH-1M:一个有134万个样本的多功能Android恶意软件数据集与丰富的元数据
Hendrio Bragança1, Diego Kreutz2, Vanderson Rocha3
1Federal University of Amazonas (UFAM), Institute of Computing, Manaus-AM, 69.077-000, Brazil. hendrio.luis@icomp.ufam.edu.br.
Scientific data
|December 31, 2025
概括
本研究介绍了MH-1M,这是一个大型的Android恶意软件数据集,用于高级研究. 它有助于通过全面的数据和分析来了解不断发展的恶意软件威胁.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 数据科学数据科学数据科学
背景情况:
- 安卓恶意软件对移动安全构成重大和不断发展的威胁.
- 现有的数据集可能缺乏高级恶意软件分析所需的规模或细节.
研究的目的:
- 介绍MH-1M,一个全面的数据集,用于Android恶意软件研究.
- 通过开放数据访问,促进对Android恶意软件的高级分析.
主要方法:
- 编制了一个 1,340,515 个 Android 应用程序的数据集.
- 利用VirusTotal API与多个检测引擎进行恶意软件分类.
- 提取了每个应用程序的功能和收集了广泛的元数据.
主要成果:
- MH-1M数据集包含超过 130 万个 Android 应用程序.
- 数据集包括全面的元数据和VirusTotal分析结果.
- 在Figshare,Harvard Dataverse和GitHub仓库中提供超过400GB的数据.
结论:
- MH-1M数据集是研究当前Android恶意软件风景的宝贵资源.
- 对这种大规模数据集的开放访问将推进Android恶意软件研究和防御策略.
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