Feature importance in mobile malware detection
This work addresses feature selection for mobile malware detection, which is an incremental improvement for researchers and practitioners in cybersecurity.
The study tackled the problem of identifying which app features are most important for mobile malware detection on Android by analyzing datasets like Drebin, VirusShare, and AndroZoo, and it ranked feature importance using the Information Gain algorithm.
The topic of mobile malware detection on the Android platform has attracted significant attention over the last several years. However, while much research has been conducted toward mobile malware detection techniques, little attention has been devoted to feature selection and feature importance. That is, which app feature matters more when it comes to machine learning classification. After succinctly surveying all major, dated from 2012 to 2020, datasets used by state-of-the-art malware detection works in the literature, we analyse a critical mass of apps from the most contemporary and prevailing datasets, namely Drebin, VirusShare, and AndroZoo. Next, we rank the importance of app classification features pertaining to permissions and intents using the Information Gain algorithm for all the three above-mentioned datasets.