metaNet, an interpretable unknown malware identification method with a novel meta-features mining algorithm
This project is the supporting material of the paper titled "metaNet: Interpretable Unknown Mobile Malware Identification with a Novel Meta-features Mining Algorithm", including: dataset, test results, source code, etc.
The folder "Virustotal" includes the detection results of tools on virustotal.
The folder "KFeatures" illustrates the first K-dimensional features we used.
The folder "Code" includes the source code of metaNet and its installation and usage tutorials.
The folder "DApps" includes the DApp experiment files such as the traffic dataset and feature extraction script.
The folder "examples" describes the distinctive features of other malware categories.