Data Privacy Quantification using Multifaceted App-Sensor Mobile Data Collector tool (AMoDaC) for Smartphone

Abstract

In this correspondence, the user privacy and data sensitivity quantification in smartphone environment is considered. The smartphone applications behaviour and user usage behaviour is monitored using an App-Sensor Mobile Data Collector (AMoDaC) tool. This tool can be used to analyse many aspects related to smartphone environment and user data. In this study, a thorough detail on how the tool was developed is presented. The tool monitors and collects significant information such as application name, application size, user data size, total size of application allocated in the phone storage, time spent on each application, permissions and its’ value, and the risk posed by each application. An experiment is carried out in a real environment to test the efficiency of the tool. From the experiment, the tool is efficient in quantifying user privacy and data sensitivity in a smartphone environment. The risk posed by each application is different for each user, although they use the same application. This is due to the usage behaviour of the user instead of the application behaviour. Thus, the multifaceted tool provides result showing that both user applications and system applications pose risk to the user according to their usage behaviour.