Volume 11 • Issue 2 • PP: 01–04 • 2026
Guardian Light: An Edge-Resilient Fail-Safe Mechanism for IoT Smart Lighting Against DDoS and Network Partitions
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© 2026 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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New cybersecurity and operational resilience issues have been brought about by the growing use of cloud managed
smart street lighting in metropolitan settings, especially in the event of network partitioning and Distributed Denial of Service (DDoS) assaults. Current systems still rely mostly on centralized cloud control, which creates a single point of failure that might compromise public safety and interfere with vital lighting functions. In the context of the author’s Streetlight-as-a-Service (SLaaS) framework, where streetlights operate as intelligent, service-capable infrastructure nodes rather than discrete lighting devices, this paper proposes Guardian Light, an edge-resilient fail-safe mechanism for intelligent street lighting. The suggested design uses AWS IoT Core, AWS IoT Device Defender, and AWS IoT Greengrass to combine device-side autonomous governance with cloud-side anomaly detection. With the help of an internal real-time clock, state-aware failover logic, persistent offline scheduling, and local threshold monitoring, Guardian Light makes it possible for lighting nodes to continue operating safely and consistently even in the event that malicious traffic is discovered or cloud connectivity is compromised. The study emphasizes how current smart lighting research goes beyond energy saving and scheduling to cyber-resilient operational continuity through the integration of edge intelligence and service-oriented streetlight design. By doing this, the study offers a workable and theoretically sound solution to improve the autonomy, security, and dependability of next-generation SLaaS-enabled smart city systems.
Keywords
References
[1] M. Mahoor, Z. S. Hosseini, A. Khodaei, A. Paaso, and D. Kushner, “State-of-the-art in smart streetlight systems: a review,” IET Smart Cities, vol. 2, no. 1, pp. 24–33, 2020.
[2] S. Khemakhem and L. Krichen, “A comprehensive survey on an iot-based smart public street lighting system application for smart cities,” Franklin Open, vol. 8, p. 100142, 2024.
[3] P. Francik, M. Poplawski, S. N. G. Gourisetti, P. O’Connell, C. Younkin, T. Ashley, and G. Seppala, “A cybersecurity threat profile for a connected lighting system,” Pacific Northwest National Laboratory, Richland, WA, USA, Tech. Rep., 2022.
[4] A. Pakmehr, A. Asmuth, N. Taheri, and A. Ghaffari, “Ddos attack detection techniques in iot networks: a survey,” Cluster Computing, vol. 27, no. 10, pp. 14 637– 14 668, 2024.
[5] L. Kong, J. Tan, J. Huang, G. Chen, S. Wang, X. Jin, P. Zeng, M. Khan, and S. K. Das, “Edge-computingdriven internet of things: A survey,” ACM Computing Surveys, vol. 55, no. 8, p. 174, 2023.
[6] Amazon Web Services, “AWS IoT Greengrass,” AWS Documentation. Available: https://aws.amazon.com/ greengrass/.
[7] ——, “Detect – AWS IoT Device Defender,” AWS IoT Device Defender Developer Guide. Available: https: //aws.amazon.com/iot-device-defender/.
[8] S.-H. Lee, Y.-L. Shiue, C.-H. Cheng, Y.-H. Li, and Y.-F. Huang, “Detection and prevention of ddos attacks on the iot,” Applied Sciences, vol. 12, no. 23, p. 12407, 2022.
[9] G. Gagliardi, D. Carotenuto, L. Nardiello, A. G. M. Strollo, and G. P. Saggese, “Advanced adaptive street lighting systems for smart cities,” Smart Cities, vol. 3, no. 4, p. 71, 2020.
[10] G. Pasolini, P. Toppan, A. Toppan, R. Bandiera, M. Mirabella, F. Zabini, D. Bonata, and O. Andrisano, “Comprehensive assessment of context-adaptive street lighting: Technical aspects, economic insights, and measurements from large-scale, long-term implementations,” Sensors, vol. 24, no. 18, p. 5942, 2024.
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