Work

MH-1M: One of The Most Comprehensive and Up-to-Date Dataset for Advanced Android Malware Detection

Year: 2024

Type: conference-paper

Abstract: We introduce MH-1M, one of the most comprehensive and up-to-date dataset for advanced Android malware research. This dataset includes 1,340,515 applications, covering diverse features and extensive sets of metadata. For precise malware assessment, we utilize the VirusTotal API, integrating multiple detection methods to ensure reliable outcomes. Our GitHub repository offers users access to the processed dataset and associated metadata, totaling over 400GB. This includes comprehensive outputs from the feature extraction process and VirusTotal metadata files. Our findings underscore the important role of the MH-1M dataset as an invaluable resource for understanding the evolving landscape of malware.

DOI: 10.5753/sbseg.2024.241632

Authors: Hendrio Bragança, Vanderson Rocha, Joner Assolin, Diego Kreutz, Eduardo Feitosa

Institutions: Universidade Federal do Amazonas, Universidade Federal do Pampa

Language: English

Topic: Advanced Malware Detection Techniques

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

OpenAlex ID: W4402984117

FWCI:

Cites: 12

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Related to: 10