Visible to the public A Simulation Study on Smart Grid Resilience Under Software-Defined Networking Controller Failures

TitleA Simulation Study on Smart Grid Resilience Under Software-Defined Networking Controller Failures
Publication TypeConference Paper
Year of Publication2016
AuthorsGhosh, Uttam, Dong, Xinshu, Tan, Rui, Kalbarczyk, Zbigniew, Yau, David K.Y., Iyer, Ravishankar K.
Conference NameProceedings of the 2Nd ACM International Workshop on Cyber-Physical System Security
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4288-9
Keywordsattacks, cps resiliency, Cyber Dependencies, faults, Metrics, Neural Network, Neural networks, neural networks security, policy-based governance, pubcrawl, Resiliency, Smart grid, Smart Grid Privacy, software-defined networking

Riding on the success of SDN for enterprise and data center networks, recently researchers have shown much interest in applying SDN for critical infrastructures. A key concern, however, is the vulnerability of the SDN controller as a single point of failure. In this paper, we develop a cyber-physical simulation platform that interconnects Mininet (an SDN emulator), hardware SDN switches, and PowerWorld (a high-fidelity, industry-strength power grid simulator). We report initial experiments on how a number of representative controller faults may impact the delay of smart grid communications. We further evaluate how this delay may affect the performance of the underlying physical system, namely automatic gain control (AGC) as a fundamental closed-loop control that regulates the grid frequency to a critical nominal value. Our results show that when the fault-induced delay reaches seconds (e.g., more than four seconds in some of our experiments), degradation of the AGC becomes evident. Particularly, the AGC is most vulnerable when it is in a transient following say step changes in loading, because the significant state fluctuations will exacerbate the effects of using a stale system state in the control.

Citation Keyghosh_simulation_2016