1*Fuad Hasan Shishir, 2Md Zahid Hasan, 3Md Ekramul Haque
1North China Electric Power University, Electrical Engineering and it’s Automation, China
2 Fulton Montgomery Community college, Computer Networking & Cyber Security,
3 Hohai University, College of Energy and Electrical Engineering, Nanjing, China
fuadhasanshishir98@gmail.com; mdzahidhasan205878@gmail.com; ekramulhaque.hhu100@gmail.com;
Abstract
With the development of advanced information and communication technology, traditional pow-er grids have been transformed into smart grids. An important feature of smart grids is the mutu-al influence between information systems and physical systems, forming a highly coupled power information physical system, which makes smart grids face more severe information security threats than traditional grids. False Data Injection Attack (FDIA) is an emerging form of covert power grid attacks. The paper comprehensively discusses the attack model, suppression schemes, and impact of false data injection on smart grids, and the topic has practical signifi-cance.The main work of the paper includes the following aspects: Firstly, the paper provides an overview of the basic concepts and key technologies of smart grids, as well as information securi-ty issues. Next, we will comprehensively discuss the FDIA model and its classification. Then, a neural network-based FDIA suppression model was designed and simulated for testing. Finally, the impact of FDIA on smart grids was comprehensively discussed. The main contribution of the paper is the design of a system model for FDIA detection, localization, and data recovery based on a neural network framework. The results of the paper can provide reference for a comprehen-sive exploration of the impact of FDIA on smart grids.
Keywords: smart grid, false data injection attack, deep neural net
Fuad Hasan Shishir, Md Zahid Hasan, Md Ekramul Haque, 2025, “Examination of the Effects of False Data Injection Attacks on Smart Grid”, https://doi.org/10.7910/DVN/D5XIZW, Harvard Dataverse, V1