Infrastructure for collecting data and simulating security threats in the internet of things network

The implementation of the internet of things technologies in the rocket-space industry requires increased security measures for information and communication processes. Existing intrusion detection systems are unable to take into account the heterogeneity of the network structure and the scale of information circulating between devices. To solve this problem, intrusion detection systems use an anomaly method, which requires a large number of representative data sets. The authors have reviewed public datasets that can be used to build an anomaly detection system. They contain information from artificial simulation medium or isolated environments with simulated devices, include examples that are not directly related to the internet of things, and do not take into account the dynamic nature of traffic changes. In this paper, we present a new infrastructure that will avoid these drawbacks. It collects data on the functioning of a real Internet of Things network and allows testing its stability to typical attacks. We use the MQTT (message queuing telemetry transport) application protocol and software platforms that support information interaction based on the publisher-subscriber pattern. The infrastructure contains devices that monitor technological rooms with telecommunications equipment, brokers with various security policy settings, applications for data control and analysis, software agents for collecting network traffic and threat simulators that perform attacks on network nodes from single sources or in a distributed environment. Researchers will be able to use the data collected in the infrastructure for cybersecurity analysis to create reliable IoT-based solutions needed to implement this technology in knowledge-intensive space systems production.