Understanding Cybersecurity Challenges and Detection Algorithms for False Data Injection Attacks in Smart Grids

In Smart grid (SG), cyber-physical attacks (CPA) are the most critical hurdles to the use and development. False data injection attack (FDIA) is a main group among these threats, with a broad range of methods and consequences that have been widely documented in recent years. To overcome this challenge, several recognition processes have been developed in current years. These algorithms are mainly classified into model-based algorithms or data-driven algorithms. By categorizing these algorithms and discussing the advantages and disadvantages of each group, this analysis provides an intensive overview of them. The Chapter begins by introducing different types of CPA as well as the major stated incidents history. In addition, the chapter describes the use of Machine Learning (ML) techniques to distinguish false injection attacks in Smart Grids. A few remarks are made in the conclusion as to what should be considered when developing forthcoming recognition algorithms for fake data injection attacks.