Gotham Testbed: A Reproducible IoT Testbed for Security Experiments and Dataset Generation

Abstract

The scarcity of available Internet of Things (IoT) datasets remains a limiting factor in developing machine learning based security systems. Static datasets get outdated due to evolving IoT threat landscape. Meanwhile, the testbeds used to generate them are rarely published. This paper presents the Gotham testbed, a reproducible and flexible network security testbed, implemented as a middleware over the GNS3 emulator, that is extendable to accommodate new emulated devices, services or attackers. The testbed is used to build an IoT scenario composed of 100 emulated devices communicating via MQTT, CoAP and RTSP protocols in a topology composed of 30 switches and 10 routers. The scenario presents three threat actors, including the entire Mirai botnet lifecycle and additional red-teaming tools performing DoS, scanning and various attacks targeting the MQTT and CoAP protocols. The generated network traffic and application logs can be used to capture datasets containing legitimate and attacking traces. We hope that researchers can leverage the testbed and adapt it to include other types of devices and state-of-the-art attacks to generate new datasets that reflect the current threat landscape and IoT protocols. The source code to reproduce the scenario is publicly accessible.