As the use of Internet of Things (IoT) increases every day, False Data Injection Attacks (FDIA) pose a significant risk to today's technology. Attackers can influence state estimations without the need to use traditional Bad Data Detection (BDD) methods by changing measurement data. This paper examines FDIA models and study their potential influence on grid stability. In addition, it assesses simulated attack scenarios using an IEEE 14-bus test system. It was found that an undetected FDIA can change critical operational parameters and coefficients such as bus voltage levels by up to 5% without being noticed. As a result, it necessary to make some good strategies to detect any threat. Secured communication protocols and abnormally detection using machine learning may be used in the future.

False Data Injection Attacks (FDIA), Internet of Things (IoT), Bad Data Detection (BDD), Cyber security