2014 · 13 citations · 9 references
Mobile SecurityInternet Traffic AnalysisEngineeringInformation SecurityNetwork ManagementInternet Of ThingsAdvanced NetworkingNetwork SecurityNetwork VirtualizationSoftware-defined NetworkingVirtualization SecurityData PrivacyComputer ScienceMobile ComputingEdge RouterNetwork Functions VirtualizationData SecurityMobile Computing SystemMobile AppsCryptographyEdge ComputingCloud Computing
Due to the increasing popularity of smartphones and tablets, mobile apps are becoming the preferred portals for users to access various network services in both residential and enterprise environments. Predominantly using generic HTTP or HTTPS protocols, traffic from different mobile apps is largely indistinguishable. This loss of visibility into mobile app traffic brings new challenges to network management and traffic analysis. It has became very hard to implement network policies based on the differentiation between traffic from compliant and non-compliant mobile apps. This paper presents a system that not only provides network administrators the much desired capability of enforcing policies on mobile app traffic, but also does that at a fine per-user granularity. The proposed system takes a Network Functions Virtualization (NFV) approach and virtualizes an edge router into multiple virtual data planes. Specifically, each data plane serves solely to one particular user and consists of user-specific virtualized network functions. The independence of the virtual data planes facilitates enforcing network policies at the per-user level. To enable policy enforcement on mobile apps, our system includes a sophisticated mobile app identification module to recognize traffic from different apps using preloaded traffic signatures. By exploiting TLS proxying, our system can even enforce policies on those mobile apps adopting traffic encryption. We have implemented a prototype of the proposed system as a wireless access point (AP) using a commodity small form factor PC. Our preliminary experimental evaluations show that the system can scale to modest number of users without much impacting user experience in using the network.
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