Resiliency-Aware Deployment of SDN in Smart Grid SCADA: A Formal Synthesis Model

The supervisory control and data acquisition (SCADA) network in a smart grid requires to be reliable and efficient to transmit real-time data to the controller, especially when the system is under contingencies or cyberattacks. Introducing the features of software-defined networks (SDN) into a SCADA network helps in better management of communication and deployment of novel grid control operations. Unfortunately, it is impossible to transform the overall smart grid network to have only SDN-enabled devices overnight because of budget and logistics constraints, which raises the requirement of a systematic deployment methodology. In this article, we present a framework, named SDNSynth, that can design a hybrid network consisting of both legacy forwarding devices and programmable SDN-enabled switches. The design satisfies the resiliency requirements of the SCADA network, which are determined with respect to a set of pre-identified threat vectors. The resiliency-aware SDN deployment plan primarily includes the best placements of the SDN-enabled switches (replacing the legacy switches). The plan may include one or more links to be installed newly to provide flexible or alternate routing paths. We design and implement the SDNSynth framework that includes the modeling of the SCADA topology, SDN-based resiliency measures, resiliency threats, mitigation requirements, the deployment budget, and other constraints. It uses satisfiability modulo theories (SMT) for encoding the synthesis model and solving it. We demonstrate SDNSynth on a case study of an example small-scale network. We also evaluate SDNSynth on different synthetic SCADA systems and analyze how different parameters impact each other. We simulate the SDNSynth suggested networks in a Mininet environment, which demonstrate the effectiveness of the deployment strategy over traditional networks and randomly deployed SDN switches in terms of packet loss and recovery time during network congestions.