Feature importance in mobile malware detection

Authors: Vasileios Kouliaridis, Georgios Kambourakis, Tao Peng
Published: 2020-07-27 | Updated: 2020-08-28

Source: https://arxiv.org/abs/2008.05299

PDF: https://arxiv.org/pdf/2008.05299

AIにより推定されたラベル

特徴重要度分析 データセット分析 マルウェア検出手法

※ こちらのラベルはAIによって自動的に追加されました。そのため、正確でないことがあります。
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Abstract

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.