An Machine Learning Model for forecasting Malware in Android System

Abstract

Android overlay enables one app to draw over other apps by creating an extra View layer atop the host View, which nevertheless can be exploited by malicious apps (malware) to attack users. To combat this threat, prior countermeasures concentrate on restricting the capabilities of overlays at the OS level while sacrificing overlays usability; recently, the overlay mechanism has been substantially updated to prevent a variety of attacks, which however can still be evaded by considerable adversaries. Malware remains a big threat to cyber security, calling for machine learning based malware detection. While promising, such detectors are known to be vulnerable to evasion attacks. This paper presents review of android malware prediction using machine learning techniques.