Risk-Rating Framework for Mobile Applications

Systems, methods and computer readable medium for training a risk rating system for assessing a risk of a mobile application are disclosed. One or more features representing operational characteristics of mobile applications and malware are extracted. A first learning classifier and a second learning classifier are trained using the extracted features. A machine learning risk rating model is generated, based on the combination of the first learning classifier and the second learning classifier to calculate a risk rating based on the features and a correlation of the features. Systems, methods, and computer readable medium for assessing a risk for a mobile application are also disclosed. One or more features of a mobile application are extracted. A learning classifier is applied to the extracted features. A risk rating is determined based on the result of the classifier.