# Comprehensive Survey and Taxonomies of False Injection Attacks in Smart Grid: Attack Models, Targets, and Impacts

arXiv: https://arxiv.org/abs/2103.10594 · HTML: https://mlsanity.com/paper/2103.10594/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Mar 2021.

## Built on by (most cited first, 6 of 6)

- [False Data Injection Threats in Active Distribution Systems: A Comprehensive Survey](https://mlsanity.com/paper/2111.14251/) (2021)
- [Bi-Level Poisoning Attack Model and Countermeasure for Appliance Consumption Data of Smart Homes](https://mlsanity.com/paper/2107.02897/) (2021)
- [FedDiSC: A Computation-efficient Federated Learning Framework for Power Systems Disturbance and Cyber Attack Discrimination](https://mlsanity.com/paper/2304.03640/) (2023)
- [Anomaly Detection Dataset for Industrial Control Systems](https://mlsanity.com/paper/2305.09678/) (2023)
- [Clustered Federated Learning for Generalizable FDIA Detection in Smart Grids with Heterogeneous Data](https://mlsanity.com/paper/2507.14999/) (2025)
- [Short-Term Forecasting of Energy Production and Consumption Using Extreme Learning Machine: A Comprehensive MIMO based ELM Approach](https://mlsanity.com/paper/2508.12764/) (2025)

## Abstract (arXiv)

Smart Grid has rapidly transformed the centrally controlled power system into a massively interconnected cyber-physical system that benefits from the revolutions happening in the communications (e.g. 5G) and the growing proliferation of the Internet of Things devices (such as smart metres and intelligent electronic devices). While the convergence of a significant number of cyber-physical elements has enabled the Smart Grid to be far more efficient and competitive in addressing the growing global energy challenges, it has also introduced a large number of vulnerabilities culminating in violations of data availability, integrity, and confidentiality. Recently, false data injection (FDI) has become one of the most critical cyberattacks, and appears to be a focal point of interest for both research and industry. To this end, this paper presents a comprehensive review in the recent advances of the FDI attacks, with particular emphasis on 1) adversarial models, 2) attack targets, and 3) impacts in the Smart Grid infrastructure. This review paper aims to provide a thorough understanding of the incumbent threats affecting the entire spectrum of the Smart Grid. Related literature are analysed and compared in terms of their theoretical and practical implications to the Smart Grid cybersecurity. In conclusion, a range of technical limitations of existing false data attack research is identified, and a number of future research directions is recommended.