False data injection attacks against state estimation in electric power grids

Abstract

A power grid is a complex system connecting electric power generators to consumers through power transmission and distribution networks across a large geographical area. System monitoring is necessary to ensure the reliable operation of power grids, and state estimation is used in system monitoring to best estimate the power grid state through analysis of meter measurements and power system models. Various techniques have been developed to detect and identify bad measurements, including interacting bad measurements introduced by arbitrary, nonrandom causes. At first glance, it seems that these techniques can also defeat malicious measurements injected by attackers. In this article, we expose an unknown vulnerability of existing bad measurement detection algorithms by presenting and analyzing a new class of attacks, called false data injection attacks , against state estimation in electric power grids. Under the assumption that the attacker can access the current power system configuration information and manipulate the measurements of meters at physically protected locations such as substations, such attacks can introduce arbitrary errors into certain state variables without being detected by existing algorithms. Moreover, we look at two scenarios, where the attacker is either constrained to specific meters or limited in the resources required to compromise meters. We show that the attacker can systematically and efficiently construct attack vectors in both scenarios to change the results of state estimation in arbitrary ways. We also extend these attacks to generalized false data injection attacks , which can further increase the impact by exploiting measurement errors typically tolerated in state estimation. We demonstrate the success of these attacks through simulation using IEEE test systems, and also discuss the practicality of these attacks and the real-world constraints that limit their effectiveness.

Cross-Level Detection Framework for Attacks on Cyber-Physical Systems

“…The majority of this research proposes defending attacks at the network or process level. The basis for the attack model used for the physical experiment described in Section 8 was the FDI concept introduced in [21]. One form of FDI attack known as a replay attack [22] shows that attackers can mislead traditional fault detectors while still providing arbitrary input to controllers.…”

Climate Change and Energy Management Strategies

“…It is worth to mention that both power grids and buildings have been prone to cyber-attack even before their interconnection in the form of the internet of things. However, due to the increased points of entries in a heterogeneous network with interconnected devices and their different capabilities, and because of distributed, multi-agent control system in contrast with the hierarchical control system in conventional networks, it is complicated to provide a strong and uniform protection for the entire smart network [9] [11]. Figure 2 provides a comparison between conventional and smart methods of energy metering.…”

Cyber Risk Assessment of Transmission Lines in Smart Grids

“…Unfortunately, this detection approach cannot ensure the integrity of the data transmitted to the control center. It has been shown in [1] that a wise attacker can construct the coordinated false data z "H∆θ to avoid being detected by the residual checking. Thus, such an attack is called undetectable false data injection attack.…”

“…Consequently, SCADA systems are becoming the primary target of cyber-attacks. It has been shown that an attacker can compromise the Direct Current (DC) state estimation by launching false data injection attacks, which could be undetectable if the attacker can construct the false data that obeys Kirchhoff's Current Law (KCL) and Kirchhoff's Voltage Law (KVL) based on the full network information of the power grid [1].…”

“…Note that there is a strong condition in [1][2][3][4][5][6][7][8][9][10][11][12][13] that the full network information of a power network is assumed to known to an attacker. This strong condition would make the proposed attacking model impractical.…”