LEDGE: Leveraging Edge Computing for Resilient Access Management of Mobile IoT

Due to the blooming of Internet of Things (IoT), heterogeneous IoT mobile devices emerge to connect the network infrastructure. Traditional mobile access system faces several challenges arising from these IoT devices: 1) centralized controllers are distant from the end devices, 2) inefficient access control of heterogeneous IoT devices, and 3) insufficient authentication and monitoring for IoT devices. In order to tackle the challenges from IoT devices on mobile access control and scalable access monitoring, we present LEDGE, an agile and secured software-defined edge computing system for resilient access management of mobile IoT. In a nutshell, our LEDGE is a synergy of an efficient location authentication method to secure communication between each IoT mobile device and access point (AP) pair, an optimal AP assignment scheme to satisfy IoT flow requests, a Personal AP protocol for scalable access, and a deep learning model for anomaly detection. We prototype our system, and realistic testbed experiments demonstrate that LEDGE could achieve promising results in mobile IoT.

Automated summary

In response to the challenges posed by IoT devices on mobile access control and monitoring, LEDGE is introduced as a secure and agile software-defined edge computing system. By incorporating efficient location authentication, optimal access point assignment, scalable Personal AP protocol, and anomaly detection through deep learning, LEDGE demonstrates promising results in mobile IoT access management.