Cyber security of smart grid state estimation: attacks and defense mechanisms

Abstract

In this chapter, we looked into the problem of malicious FDIAs in power grid state estimation. We proposed stealth attack construction strategies for different scenarios and also introduced the countermeasures. The results demonstrate that the proposed random attack construction algorithm can generate extremely sparse attack vectors with high probabilities with consideration of the noise in measurements. Traditional successful attacks tend to compromise a number of measurements, which exceeds a certain value. The proposed algorithm can construct undetectable attacks which only compromise a much smaller numbers of measurements than this known value. The targeted attack construction method is evaluated considering different percentages of state variables are targeted and different number of measurements are protected. The results show that attack vectors in this scenario cannot be extremely sparse, unless only an extremely small number of state variables are targeted. It also demonstrates that targeted stealth attack vectors do not exist when a number of measurements are protected from being modified. An efficient protection scheme is proposed in this chapter to find an effective measurement protection subset to defend from the stealth attacks. The simulation results have demonstrated that the proposed algorithm can find protection subsets with the same size as that from brute-force method in nearly all cases. More importantly, the algorithm is quick, and thus feasible in practice when the power system is large. Additionally, a detection algorithm is introduced to detect the stealth attacks as well as other false data. This algorithm considers the case in which only partial measurements are collected in the presence of noise. The performance is demonstrated via the simulation results based on IEEE test power systems.