Towards 3-level hybrid security model for Android Operating Systems

The extensive use and rapid growth in popularity of Android phones have attracted the malware developer's attention. Due to this reason, malware attacks on Android devices are increasing every year. In this research, firstly we have investigated existing anti-malware techniques and identified their limitations. Secondly, we provided the description of a novel 3-level hybrid malware detection model for Android operating systems, which is an open-ended project and is currently under development. It is designed to ensure accurate detection of malware through the combination of i) Static & Dynamic Analysis; ii) Local & Remote Host; and iii) Machine Learning Intelligence. Through experimental results, it is shown that the 3-level hybrid malware detection model can achieve 98.5% detection rate, which is higher in comparison to the detection rate of Drebin.