The thesis addresses the issue of cybersecurity in the Internet of Things (IoT). The main objective was to develop and test a specialized high-interaction honeypot based on the concept of a smart thermostat's digital twin. The developed tool realistically simulates the operation of a real device using thermodynamic models and dynamic responses to environmental changes.
The implemented simulation includes seasonal and daily temperature cycles, natural heat exchange, and an HVAC system with hysteresis. The smart thermostat features multiple API endpoints for reading and configuring various operational parameters. The thesis also covers key concepts, including the history, operation of different types of honeypots and strategic placement within a network. It provides a detailed description of the development process, including the choice of technologies such as Python, the Flask framework, and Docker, as well as the technical challenges overcome in creating a convincing simulation.
The system was deployed on a server with a public IP address and tested for three weeks, during which it was subjected to 14,578 attacks from 808 unique IP addresses. The analysis revealed that the majority of attacks originated from data centers, with 58.61%} of the attackers identified as automated scanners. The malicious pattern detection system successfully intercepted various attack techniques, such as command injection and malware infection attempts.
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