Smart Traps for Smart Systems: Scalable Honeynets for IIoT Cybersecurity

Honeypots serve as decoy systems that attract and monitor intruders, offering insights into their behavior. When interconnected, these honeypots form honeynets, simulating high-value environments to engage attackers and facilitate deeper analysis. However, in Industrial Internet of Things (IIoT) networks, deploying honeypots presents challenges such as static configurations, lack of network context, and difficulties in scaling.In this paper, we introduce TrapNet, a scalable, lightweight honeynet framework specifically designed for IIoT environments. TrapNet combines compact, on-site honeypots with large-scale, adaptive honeynets deployed on fog and cloud infrastructures using microservices. This approach enables fast deployment, scalability, and flexibility, providing an effective solution for IIoT cybersecurity. Our experimental results show that TrapNet efficiently detects intrusions while maintaining low resource overhead. Additionally, all code and configurations used in this study are publicly available, fostering further research and innovation in honeynet design and IIoT security.