Static detection of Android malware based on improved random forest algorithm

Abstract

In recent years, smart phone becomes more and more popular. At the same time, the security threat of smart phone is growing. According to “Motive Security Labs Malware Report-H1 2015” [1] report, the number of Android malware is growing year by year. Many researchers focus on the security of Android applications based on permission. Felt et al. [2] designed the stowaway tool to detect the application's over-privilege. This tool can also identify and quantify the over-privilege triggered by developer errors. Enck et al. [3] proposed a security mechanism called Kirin. The Kirin consisted of nine permission rules. The more rules the application has, the more dangerous it is. But few studies use two-layer models for detection to improve accuracy.