Revealing a New Vulnerability of Distributed State Estimation: A Data Integrity Attack and an Unsupervised Detection Algorithm

Alireza Shefaei,Behnam Mohammadi-Ivatloo,Mostafa Mohammadpourfard,Yang Weng

doi:10.1109/tcns.2021.3091631

Abstract

This article proposes a distributed false data injection attack (FDIA) by attacking to the boundary buses in an interconnected power system. The proposed attack utilizes the measurements corresponding to a set of boundary buses in each neighboring areas to inject arbitrary errors to the estimated states of those buses. It is demonstrated that the attack not only gets through the robust distributed estimators but also bypasses the convergence-based detection methods. Furthermore, in an illustrative example, the differences in the attack with the conventional FDIA are briefly explained. Then, finding the optimal attack vector to minimize the maximum difference between the per area errors by considering the attacker’s limitations is formulated as a mixed-integer second-order cone programming problem. Finally, an unsupervised machine learning-based detection method is proposed utilizing a kernel density estimation technique along with statistical measures. This follows an outlier detection to filter out attacks. To show the performance of the detector, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$n-1$</tex-math></inline-formula> contingency, which changes the probability distribution of data is analyzed. The proposed attack and detector are tested on various IEEE systems such as IEEE 14-bus and IEEE 118-bus test systems and the results are discussed.

Highlights

D ECENTRALIZED task management is becoming the main solution in the interconnected power grids
As it is explained in Appendix A, the proposed attack can sail through the bad data detector of [5]
It should be noted that none of them will able to obtain per area error of their neighborhoods in the condition of independent operation of areas

Summary

Introduction

D ECENTRALIZED task management is becoming the main solution in the interconnected power grids. The state estimation, which is one of the essential functions in the power grid energy management system (EMS), is carried out by the EMS of each area of the interconnected system. While the state estimation is typically performed hierarchically in the interconnected power systems, there is a growing interest in a fully distributed state estimation (DSE) for the future intelligent grids as it eliminates the need for a central unit. The main idea of the DSE methods is the estimation of states of each area using that area’s measurements and sharing the states of boundary buses between neighboring areas. A DSE method for restructured power systems has been proposed in [1] and its practical aspects have been examined. The authors in [3]

Methods

Results

Conclusion