# Enhancing Cybersecurity in Smart Grids: False Data Injection and Its Mitigation
## 3 Classifications of Cyber-Attacks in SGs
### False Data Injection Attacks (FDIA)
Due to its high level of importance, FDIAs are currently the most studied cyber-physical SG security attacks [105]. For example; two versions of FDIA scenarios have been found in [56] where in Generalized and Random FDIA, an attacker uses small false data error in measurements and has some necessities for an accomplished attack, like they must comprehend the topology of the energy system to control and manipulate the measurement of the AMI. In random FDIA, attackers direct a wrong estimation. Figure 8 shows various false data injection attacks scenarios on smart grid [106]. In [107], the study is examined with the architectural structure of FDIA and divided into two mains criteria's: cyber and physical. According to [108], it only focused on the physical criteria and the extensive classification of [107] study and a new control centre model. Authors in [109] finished the work in [108] and their formulation studied the impact of state estimation of FDIAs on electricity market operations. In the AC power transmission system, FDI attacks on the SE are summarized in [92; 110; 111] as a stealthy FDI attack with two steps. The first, \"Intrusion into the System\" is examined. If the attacker who trying to intervene in the system is on the outside of the system, he attacks the system using one or more of the usual cyber hacks by endangering the wired or wireless communication channel. In addition to this situation, the attacker may be successful in integrating malware. In this case, the attacker may be capable of stealing system information, particularly the bus topology. The second step is \"Carry out stealthy FDI attack\" aims to perform a stealthy FDIA by changing the measurement data. The manager supposes that the data are right and also estimates the other values based on this false assumption. It causes the system to reverse and hence an incorrect condition causing malfunctions or substantial deductions. Another type of FDIA presented in [112] on power system protection suggests two targeted attack scenarios: fake safe and fake vulnerable signal attacks. The first fake protected signal attack attempts to trick the control centre into performing a required corrective acts such as load shedding and neglecting a power line peak demand by switching from an unstable to a secure state. The second fake unstable signal attack attempts to move from a safe to an insecure state in order to deceive the control centre into performing inappropriate corrective steps, thus inflating costs unnecessarily. Security-constrained economic dispatch (SCED) proposed in [112], and SCED FDIAs can be divided into two types: attack optimizing operating cost and attack causing overload. The first is to boost the cost of generation or load shedding or to make an illegitimate profit [113]. The second group aims to overwhelm power lines in order to inflict physical harm [114]. \[\hat{x}=\left(H^{\mathsf{T}}WH\right)^{-1}\!H^{\mathsf{T}}W_{Z} \tag{1}\]1 FDIA Scenarios in SG. Contingency analysis (CA) is one of the significant functions of power system security. These kinds of FDIAs are proposed in [115]; an attacker who knows network topology and system parameters can smoothly run the control algorithm to have the contingency list. CA can calculate complexity in real-time power market operations, flow-based SCED with DC assumptions. The study [115] constructs an attack vector by modifying the contingency list using both analogue and optical dimensions. The problem is modelled as a mixed-integer non-linear programming-based (MINLP) optimization problem, and the physical and economic effects of these attacks on the SG power system have been quantified. The attackers inject types, and FDIA measurement reports aim to disrupt the smart grid operation through the compromised meters and sensors [116]. FDIA attacks can disrupt the grid system state estimation and cause energy distribution false. Moreover, meters and sensors lacking tamper-resistance hardware increase the possibility to be compromised.