2022 journal article

Strategic Protection Against FDI Attacks With Moving Target Defense in Power Grids


By: Z. Zhang*, R. Deng, P. Cheng & M. Chow n

co-author countries: China 🇨🇳 United States of America 🇺🇸
author keywords: False data injection (FDI) attack; moving target defense (MTD); power system state estimation (SE)
Source: Web Of Science
Added: June 13, 2022

Moving target defense (MTD) is a new defensive strategy protecting the power system state estimation from cyberattacks. Using the distributed flexible ac transmission system (D-FACTS), MTD works by actively perturbing the branch parameters that are needed to construct the false data injection (FDI) attacks. Although there are many pioneer works on MTD, the relationship between the construction of MTD and detection of FDI attacks has not been revealed. In this article, we reveal the correlation between MTD design and FDI detection and optimize MTD’s performance in terms of detecting FDI attacks. We provide a sufficient condition for a specially designed MTD to detect and identify the FDI attack and a necessary condition for general MTDs to protect the state estimates from being independently modified. With the aim to reduce the number of measurements that can be manipulated by the attacker after MTD, we develop a heuristic algorithm to compute a near-optimal solution for the deployment of D-FACTS devices. Moreover, we prove that the coordinated design of consecutive perturbation schemes within an MTD cycle can improve the performance of MTD in terms of detecting FDI attacks. Finally, we conduct extensive simulations with the IEEE power system test cases to validate our findings.