Integration of SDN and Digital Twin for the Intelligent Detection of DoC Attacks in WRSNs
Muhammad Umar Farooq Qaisar, Weijie Yuan, Guangjie Han, Adeel Ahmed, Chang Liu, Md. Jalil Piran
TL;DR
The paper tackles the security vulnerability of wireless rechargeable sensor networks (WRSNs) to Denial of Charging (DoC) attacks during on-demand charging. It proposes a joint Software-Defined Networking (SDN) and Digital Twin (DT) framework in which the DT mirrors the WRSN in real time and the SDN controller dynamically manages charging and routing. Four probabilistic metrics—charging request patterns, energy consumption, behavioral/reputation scores, and charging behavior/efficiency—are computed at the DT layer and combined into a single maliciousness score $M_i(t)$ using weights, with a DoC decision based on a threshold $θ_{DoC}$, guiding the SDN to adjust the charging queue accordingly. The approach yields improvements in energy usage efficiency, survival rate, and detection rate, as well as optimized travel distance for mobile charging vehicles, demonstrating a practical, resilient defense for securing WRSNs in IoT deployments. Overall, the SDN–DT integration provides real-time anomaly detection and adaptive mitigation that enhances the reliability and longevity of WRSNs under malicious charging conditions.
Abstract
Wireless rechargeable sensor networks (WRSNs), supported by recent advancements in wireless power transfer (WPT) technology, hold significant potential for extending network lifetime. However, traditional approaches often prioritize scheduling algorithms and network optimization, overlooking the security risks associated with the charging process, which exposes the network to potential attacks. This paper addresses this gap by integrating Software-Defined Networking (SDN) and Digital Twin technologies for the intelligent detection of Denial of Charging (DoC) attacks in WRSNs. First, it leverages the flexibility and intelligent control of SDN, in combination with Digital Twin, to enhance real-time detection and mitigation of DoC attacks. Second, it employs four key metrics to detect such attacks including charging request patterns, energy consumption, behavioral and reputation scores, and charging behavior and efficiency. The numerical results demonstrate the superior performance of the proposed protocol in terms of energy usage efficiency, survival rate, detection rate, and travel distance.