Recent advances in the cyber-physical smart grid (CPSG) have enabled a broad range of new devices based on the information and communication technology (ICT). However, these ICT-enabled devices are susceptible to a growing threat of cyber-physical attacks. This paper performs a thorough review of the state-of-the-art cyber-physical security of the smart grid. By focusing on the physical layer of the CPSG, this paper provides an abstracted and unified state-space model, in which cyber-physical attack and defense models can be effectively generalized. The existing cyber-physical attacks are categorized in terms of their target components. We then discuss several operational and informational defense approaches that present the current state-of-the-art in the field, including moving target defense, watermarking, and data-driven approaches. Finally, we discuss challenges and future opportunities associated with the smart grid cyber-physical security.

Moving target defense (MTD) is a defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation using distributed flexible AC transmission system (D-FACTS) devices. However, existing studies neglect to address a fundamental yet critical issue, i.e., the D-FACTS placement, by assuming that all lines are equipped with D-FACTS devices. To tackle this problem, we first derive analytical necessary conditions and requirements on the D-FACTS placement for a complete MTD. Further, we propose sufficient conditions using a graph theory-based topology analysis to ensure that the MTD under the proposed D-FACTS placement has the maximum rank of its composite matrix, which is indicative of the MTD effectiveness. Based on the analytical conditions, we design D-FACTS placement algorithms by using the minimum number of D-FACTS devices to achieve the maximum MTD effectiveness. A novel MTD-based ACOPF model, in which the reactance of D-FACTS lines is introduced as decision variables, is proposed to find a trade-off between the system loss and the MTD effectiveness. Numerical results on 6-bus, IEEE 14-bus, and IEEE 118-bus systems show the efficacy of MTDs using the proposed D-FACTS placement algorithms in maximizing the composite matrix rank and detecting FDI attacks.

Moving target defense (MTD) in the power system is a promising defense strategy to detect false data injection (FDI) attacks against state estimation using distributed flexible AC transmission system (D-FACTS) devices. A hidden MTD (HMTD) is a superior MTD method, as it is stealthy to sophisticated attackers. However, the optimal planning and operation of D-FACTS devices that ensure the MTD hiddenness and maximal detection effectiveness are challenging yet unresolved issues. In this paper, we tackle these challenges by first deriving a novel hiddenness operation condition. Then, we propose an analytical sufficient condition on the D-FACTS placement for HMTDs using a graph-theory-based topology analysis. A depth-first-search-based D-FACTS placement algorithm is proposed to guarantee the MTD hiddenness while maximizing the rank of its composite matrix, i.e., an indicator of the MTD effectiveness, and covering all necessary buses. Additionally, we propose DC- and AC-HMTD operation models to determine the setpoints of D-FACTS devices. The optimization-based DC-HMTD model overcomes the drawbacks of the existing HMTD operation. The ACOPF-based HMTD operation model minimizes the generation cost to utilize the economic benefit of D-FACTS devices. Comparative numerical results on the IEEE 14-bus and IEEE 57-bus systems show the efficacy of the proposed planning and operation approaches.

Nanogrids are customer deployments that can generate and inject electricity into the power grid. These deployments are based on behind-the-meter renewable energy resources and are labeled as “prosumer setups”, allowing customers to not only consume electricity, but also produce it. A residential nanogrid is comprised of a physical layer that is a household-scale electric power system, and a cyber layer that is used by manufacturers and/or grid operators to remotely monitor and control the nanogrid. With the increased penetration of renewable energy resources, nanogrids are at the forefront of a paradigm shift in the operational landscape and their correct operation is vital to the electric power grid. In this paper, we perform a cybersecurity assessment of a state-of-the art residential nanogrid deployment. For this purpose, we deployed a real-world experimental nanogrid setup that is based on photovoltaic (PV) generation. We analyzed the security and the resiliency of this system at both the cyber and physical layers. While we noticed improvements in the cybersecurity measures employed in the current nanogrid compared to previous generations, there are still major concerns. Our experiments show that these concerns range from exploiting well-known protocols, such as Secure Shell (SSH) and Domain Name Service (DNS), to the leakage of confidential information, and major shortcomings in the software updating mechanism. While the compromise of multiple nanogrids can have a negative effect on the entire power grid, we focus our analysis on individual households and have determined through Simulink-based simulations the economic loss of a compromised deployment.

This paper introduces Moving Target Defense (MTD) in distribution system against False Data Injection (FDI) attacks on the supervisory control and data acquisition (SCADA) system. Based on the AC power flow model, a hidden MTD (HMTD) strategy is constructed in combination with network reconfiguration by minimizing the system loss and line power flow differences before and after the HMTD. The proposed HMTD-based network reconfiguration is formulated as a mixed-integer nonlinear programming (MINLP) problem. A refined Genetic Algorithm (GA) is proposed to solve it. Numerical test is conducted in a modified IEEE-66 bus system. The simulation results show that the proposed model reduces the power loss introduced by the HMTD as well as yields a stealthy MTD to the attackers. The impact of HMTD on the system performance is also compared with that of the existing MTD strategies.

Moving target defense (MTD) using distributed flexible AC transmission system (D-FACTS) devices is a promising defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation. However, all existing studies myopically perturb the reactance of D-FACTS lines without considering the system voltage stability. In this paper, we first illustrate voltage instability induced by MTDs in a three-bus system. To address this issue, we further propose a novel MTD framework that explicitly considers system voltage stability by using continuation power flow and voltage stability indices. We mathematically derive the sensitivity matrix of voltage stability index to line impedance, on which an optimization problem for maximizing voltage stability index is formulated. This framework is tested on the IEEE 14-bus and the IEEE 118-bus transmission systems, in which net load redistribution attacks are launched by sophisticated attackers. The simulation results show the effectiveness of the proposed framework in circumventing the voltage instability while maintaining the detection effectiveness of MTD. We conduct case studies with and without the proposed framework under different MTD planning and operational methods. The impacts of the proposed two methods on attack detection effectiveness and system economic metrics are also revealed.