LAUSR

In this paper, we introduce a new methodology for network access control for Android devices based on app risk assessment. Named ARANAC (which stands for Application Risk Assessment based Network Access Control), this methodology is specially tailored for scenarios using the Bring-Your-Own-Device (BYOD) policy, where the adoption of some solutions can lead to problems in security and privacy for both the employees and the business organization. ARANAC mainly relies on the analysis of an aggregate of permissions declared in the manifests of installed applications on users’ devices. The access control scheme combines three operational modules: i) a device monitoring tool, ii) a novel permission-based risk model, and iii) an anomaly-based detection machine learning module based on a methodology (called MSNM, from Multivariate Statistical Network Monitoring) that provides both detection and diagnostic capabilities. ARANAC’s novelty is in the combination of four features. Firstly, it is privacy-aware, and thus, it does not require detailed information about installed applications but only an aggregate of permissions. Secondly, it builds a normality model by combining expert knowledge with data, capturing the behavior of a complete population of mobile devices. Thirdly, it is dynamic, as permissions are updated in real time, allowing the network to re-assess access control on a continuous basis. Finally, its diagnostic capabilities allow for giving recommendations to final users so that they are capable of mitigating their risks when accessing networks. We evaluated the approach with more than 80 Android devices at a university campus network and obtained interesting results regarding security risks in the usual deployment of device apps.