# A Comprehensive Survey on Enabling Techniques in Secure and Resilient Smart Grids
## 3 Smart Grid Cyber-Physical Attacks
### False Data Injection (FDI)  
False data injection attacks have been considered one of the most challenging issues in smart grids [19]. To successfully conduct an FDI attack, the attackers must have somewhat of an understanding of the configuration of the target power system, especially the system topology [21]. At the same time, the attackers will try to temper some of the values from smart meters either physically or manipulate the measurement data to keep the residuals the same, which will not be alarmed by bad data detection [22].  
[PERSON] et al. analysed FDI attacks in detail, which can be classified by FDI attacks' targets [19]. They proposed four different targets that FDI attacks usually aim at in a smart grid system: FDI attacks on state estimation, FDI attacks on voltage control, FDI attacks on frequency control, and FDI attacks on the protection system. In state estimation, more DC state estimation cases have been studied than AC state estimation due to simplicity. An FDI attack will pose a major threat to state estimation if the critical measurement data have been manipulated. The smart grid voltage value is usually controlled by power electronics-interfaced distributed generations and rotational-based generators. Modifying the measurement of voltage and control signals among the layers will impact the voltage regulation in the smart grid. Smart grid frequency control is sensitive to active powers, frequency measurements, and reference signals, which means any FDI attacks aiming at rotor speed or angle measurements will change the frequency stability. Protecting the system design is one of the main challenges of smart grids. FDI attacks against protection systems could affect the system performance and also lead to disaster events.  
A network topology attack is one of the FDI attacks, which mainly aims to disorder the state estimation results by attacking the topology estimations. The stealthy topology attack could not only bypass bad data detection but also convince the control center of thenew network topology. In [23], the author proved that stealthy topology attacks will be able to affect the state estimation and also the real-time locational marginal price (LMP).  
Replay attacks in smart grids require attackers to gain access to PMUs first, then intercept and record the packages, including the measurements, for a period of time. At last, the attackers launch the replay attack by forwarding the captured packages to trick the smart grid and collect real measurement data for other malicious use. To sum up, a replay attack is one kind of FDI attack, which repeats stealthy data in a period to deceive the smart grid controlling system and aims at stealing electricity and causing physical damage without being detected. According to [18], reply attacks are difficult to detect by the control systems because of the limited capability of examining the cryptographic keys.  
Another type of sophisticated false data injection attack is called a zero-dynamic attack (ZDA), which requires some knowledge from the target system [24; 25]. The key element of zero-dynamic attacks is designing a residue attack signal that equals zero by adjusting the attack vectors against non-minimum phase systems [24; 25]. ZDAs can cause serious damage to a smart grid because, even if the input data are geometrically changing, there will be little change in the output stage. Sometimes, it is also called a stealthy FDI attack.  
Another well-known attack is the load redistribution attack, which only requires limited smart meters [2]. The load redistribution attack is one of the FDI attacks focusing on tempering the load buses' power injection and line power flow measurements.