Constructing risk predictors for mobile device behaviour analytics

Along with the significant growth in the popularity of mobile devices and the number of available mobileapplications, the amount of malware that harm users or compromise their privacy has also dramaticallyincreased. Smart mobile devices store a lot of personal information and, if stolen, the loss of control over thedata is typically more important than the loss of the device. Thus, the proposed research aims to investigate riskpredictors through the combination of available mobile device data in order to predict high risk usage as well asmalicious activity of a smart mobile device.