Constrained-Differential-Evolution-Based Stealthy Sparse Cyber-Attack and Countermeasure in an AC Smart Grid

As the next-generation power grids, smart grids are integrated with advanced information and communication technology (ICT) to make the grid more efficient and stable than conventional power systems. Given the mounting cyber-attack threats, these critical ICT systems create great security issues for smart grids. Additionally, the clever attackers have the ability to not only access and monitor the smart grid, but also hack it by launching well-established cyber-attacks. Thus, this article is devoted to understanding the potential stealthy cyber-attack and its countermeasure. First, this article proposes a stealthy sparse cyber-attack model in an ac smart grid by considering both the residual test-based detector and the interval-state-estimation-based detector, which is not considered in previous studies. The design model is formulated as a constrained optimization problem by minimizing the number of contaminated meters, where the characteristics of two types of detector are considered simultaneously as the constraints for the first time. A constrained differential evolution (CDE) is proposed as the solver because the optimization problem is NP-hard. Then, a generalized-cumulative-sum-based detector is developed to detect the proposed cyber-attacks, where a fractional-order state transition matrix is originally introduced into the estimator to describe the dynamics of the power system. Numerical studies illustrate the feasibility of CDE-based stealthy sparse cyber-attacks and the effectiveness of the proposed countermeasure.

Automated summary

This article investigates the stealthy cyber-attack and its countermeasure in smart grids. A stealthy sparse cyber-attack model is proposed, and a constrained optimization problem is formulated to design the model by minimizing the number of contaminated meters. A generalized-cumulative-sum-based detector is developed to detect the proposed cyber-attacks. Numerical studies demonstrate the feasibility and effectiveness of the proposed countermeasure.