Android Malware Analysis
Published: 1 September 2025| Version 2 | DOI: 10.17632/bpkksc9v5s.2
Contributors:
, Robiul Awoul Robin, Asma Sadia Tarisha, Description
The uploaded datasets (Maloid-DS and CIC-AndMal2017) contain curated information for Android malware analysis. Each dataset is provided in CSV format and includes features selected for effective classification and detection of various malware families and benign applications. Both datasets are structured with clearly labeled columns for features and class labels, enabling straightforward use for research, analysis, and benchmarking in Android malware detection studies. These CSV datasets were generated from existing publicly available Android malware datasets. We extracted and organized the relevant features into CSV format to facilitate analysis and reproducibility.
Files
Institutions
- University of New Brunswick
- United International University
Categories
Machine Learning, Internet of Things, Explainable Artificial Intelligence, Android Malware, Artificial Intelligence of Things