Experimental Dataset for FDIA Detection in an M3C Platform

1. Overview This dataset was constructed for FDIA detection in a M3C experimental platform. The data were collected under normal and attacked operating conditions and were used to train and evaluate the proposed detection model in the associated paper. 2. Data Source The dataset was generated on an experimental platform based on a typical M3C topology. All FDIA samples were injected into the information transmission links among the subcontrollers. 3. Attack Types The dataset includes the following operating cases:- No attack- Step FDIA- Ramp FDIA- Random FDIA- Stealthy FDIA 4. Input Features The input features include:1. KF-estimated capacitor voltage2. Integral of KF-estimated capacitor voltage3. Measured capacitor voltage4. Integral of measured capacitor voltage5. Reference capacitor voltageDetailed descriptions of all variables are provided in variables_description 5. Dataset Size The dataset contains 30,800 data points in total:- 10,800 normal data points- 20,000 attacked data points, including: - 5,000 step FDIA samples - 5,000 ramp FDIA samples - 5,000 random FDIA samples - 5,000 Stealthy FDIA samples 6. Notes The trained model reported in the paper was directly used for online testing. The remaining experimental settings are described in the associated manuscript. 7. Contact For questions regarding the dataset, please contact:Tingjun PanZhejiang [e-mail]