Scalable IoT Network Testbed with Hybrid Device Emulation

Abstract

In recent years, the Internet of Things (IoT) has been proliferating in various fields, such as health care, smart city, and connected autonomous vehicles. Accompanying the popularity of IoT are security attacks that exploit the vulnerabilities of many IoT devices. To build IoT anomaly detection systems, we need to collect and label a large amount data from diverse IoT scenarios, which is a time-consuming and prohibitive task if without the support of an IoT testbed. This thesis fills this urgent need by developing a scalable, flexible, safe, and secure IoT testbed. To make the testbed scalable, we need to reduce the hardware cost and make its architecture easily extendable. For this, we build a hybrid testbed consisting of real IoT devices, such as motion sensors and smart cameras, and emulated devices with Raspberry Pi. The emulated devices can replace real IoT devices with the same operational behaviour as real IoT devices but at a much lower price. Flexibility means the testbed can easily simulate different application scenarios. To make the testbed flexible, we build a dedicated data management module to facilitate the complex tasks in generating diverse traffic patterns, reproducing security attacks, collecting, visualizing, and analyzing network traffic. Testbed safety means the testbed will not cause any adverse impact to the Internet, and testbed security means protecting it from outside attacks. For safety, we carefully analyze the source code and the behaviour of launched attacks and configure a traffic filter to strictly contain the attack traffic within the testbed. For security, we scan and analyze the security of all IoT devices within the testbed to ensure no exposed vulnerability in the used devices.