Designing constraint-based False Data Injection attacks for unbalanced distribution smart grids
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Smart grid is equipped with various kinds of smart devices such as meters, sensors, and actuators, to name a few, and it can be characterized as the Internet of Things. The cyber domain of this cyber-physical system also has to deal with many cyber-threats, including the stealthy False Data Injection (FDI) attack. This man-in-the-middle data-driven attack is extremely dangerous due to its ability to disrupt the operation without being detected. The unbalanced distribution network is a highly probable target for an FDI attack due to its easy physical access. This paper will investigate an attack design scheme based on a nonlinear physical-constraint model that is able to produce an FDI attack with the same theoretical stealthy characteristic. To demonstrate the effectiveness of the proposed design scheme, simulations with the IEEE 13-node Test Feeder are conducted. The experimental results indicate that the false positive rate of the bad data detection mechanism is 100%. This figurative number opens a serious challenge for operators in maintaining the integrity of measurement data.
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