Stochastic Games for Power Grid Protection Against Coordinated Cyber-Physical Attacks (original) (raw)

A game-theoretic approach for power systems defense against dynamic cyber-attacks

International Journal of Electrical Power & Energy Systems, 2020

Technological advancements in today's electrical grids give rise to new vulnerabilities and increase the potential attack surface for cyber-attacks that can severely affect the resilience of the grid. Cyber-attacks are increasing both in number as well as sophistication and these attacks can be strategically organized in chronological order (dynamic attacks), where they can be instantiated at different time instants. The chronological order of attacks enables us to uncover those attack combinations that can cause severe system damage but remained unexplored due to the non-existent dynamic attack models. Motivated by the idea, we consider a game-theoretic approach to design a new attacker-defender model for power systems. Here, the attacker can strategically identify the chronological order in which the critical substations and their protection assemblies can be attacked in order to maximize the overall system damage. However, the defender can intelligently identify the critical substations to protect such that the system damage can be minimized. We apply the developed algorithms for these models to the IEEE-39 and 57 bus systems based on the attacker/defender budgets. Our results show the effectiveness of these models in improving the system resilience under dynamic attacks.

Cascading Failure Attacks in the Power System: A Stochastic Game Perspective

IEEE Internet of Things Journal

Electric power systems are critical infrastructure and are vulnerable to contingencies including natural disasters, system errors, malicious attacks, etc. These contingencies can affect the world's economy and cause great inconvenience to our daily lives. Therefore, security of power systems has received enormous attention for decades. Recently, the development of the Internet of Things (IoT) enables power systems to support various network functions throughout the generation, transmission, distribution, and consumption of energy with IoT devices (such as sensors, smart meters, etc.). On the other hand, it also incurs many more security threats. Cascading failures, one of the most serious problems in power systems, can result in catastrophic impacts such as massive blackouts. More importantly, it can be taken advantage by malicious attackers to launch physical or cyber attacks on the power system. In this paper, we propose and investigate cascading failure attacks (CFAs) from a stochastic game perspective. In particular, we formulate a zerosum stochastic attack/defense game for CFAs while considering the attack/defense costs, budget constraints, diverse load shedding costs, and dynamic states in the system. Then, we develop a Q-CFA learning algorithm that works efficiently in power systems without any a priori information. We also formally prove that the convergence of the proposed algorithm achieves a Nash equilibrium. Simulation results validate the efficacy and efficiency of the proposed scheme by comparisons with other state-of-the-art approaches. Index Terms-Cascading failure attacks (CFAs), Nash equilibrium, Q-CFA learning algorithm, stochastic games. I. INTRODUCTION E LECTRIC power systems are critical infrastructure and the failure of these systems can lead to severe economic, social, and security consequences. Thus, the security Manuscript

Security Games and Risk Minimization for Automatic Generation Control in Smart Grid

Lecture Notes in Computer Science, 2012

The power grid, on which most economic activities rely, is a critical infrastructure that must be protected against potential threats. Advanced monitoring technologies at the center of smart grid evolution increase its efficiency but also make it more susceptible to malicious attacks such as false data injection. This paper develops a game-theoretic approach to smart grid security by combining quantitative risk management with decision making on protective measures. Specifically, the consequences of data injection attacks are quantified using a risk assessment process based on simulations. Then, the quantified risks are used as an input to a stochastic game model, where the decisions on defensive measures are made taking into account resource constraints. Security games provide the framework for choosing the best response strategies against attackers in order to minimize potential risks. The theoretical results obtained are demonstrated using numerical examples.

Defending Mechanisms for Protecting Power Systems against Intelligent Attacks

The power system forms the backbone of a modern society, and its security is of paramount importance to nation's economy. However, the power system is vulnerable to intelligent attacks by attackers who have enough knowledge of how the power system is operated, monitored and controlled. This paper proposes a game theoretic approach to explore and evaluate strategies for the defender to protect the power systems against such intelligent attacks. First, a risk assessment is presented to quantify the physical impacts inflicted by attacks. Based upon the results of the risk assessment, this paper represents the interactions between the attacker and the defender by extending the current zero-sum game model to more generalized game models for diverse assumptions concerning the attacker's motivation. The attacker and defender's equilibrium strategies are attained by solving these game models. In addition, a numerical illustration is demonstrated to warrant the theoretical outcomes.

Risk Assessment of Malicious Attacks Against Power Systems

IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 2009

The new scenarios of malicious attack prompt for their deeper consideration and mainly when critical systems are at stake. In this framework, infrastructural systems, including power systems, represent a possible target due to the huge impact they can have on society. Malicious attacks are different in their nature from other more traditional cause of threats to power system, since they embed a strategic interaction between the attacker and the defender (characteristics that cannot be found in natural events or systemic failures). This difference has not been systematically analyzed by the existent literature. In this respect, new approaches and tools are needed. This paper presents a mixed-strategy game-theory model able to capture the strategic interactions between malicious agents that may be willing to attack power systems and the system operators, with its related bodies, that are in charge of defending them. At the game equilibrium, the different strategies of the two players, in terms of attacking/ protecting the critical elements of the systems, can be obtained. The information about the attack probability to various elements can be used to assess the risk associated with each of them, and the efficiency of defense resource allocation is evidenced in terms of the corresponding risk. Reference defense plans related to the online defense action and the defense action with a time delay can be obtained according to their respective various time constraints. Moreover, risk sensitivity to the defense/attack-resource variation is also analyzed. The model is applied to a standard IEEE RTS-96 test system for illustrative purpose and, on the basis of that system, some peculiar aspects of the malicious attacks are pointed out.

Security Analysis of Smart Grid Cyber Physical Infrastructures Using Game Theoretic Simulation

2015 IEEE Symposium Series on Computational Intelligence, 2015

Cyber physical computing infrastructures typically consist of a number of interconnected sites including both cyber and physical components. In this analysis we studied the various types and frequency of attacks that may be levied on smart grid cyber physical systems. Our information security analysis utilized a dynamic Agent Based Game Theoretic (ABGT) simulation. Such simulations can be verified using a closed form game theory analytic approach to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. We concentrated our study on the electric sector failure scenarios from the NESCOR Working Group Study. We extracted four generic failure scenarios and grouped them into three specific threat categories (confidentiality, integrity, and availability) to the system. These specific failure scenarios serve as a demonstration of our simulation. The analysis using our ABGT simulation demonstrates how to model the electric sector functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the cyber physical infrastructure network with respect to CIA.

Defense of Cyber Infrastructures Against Cyber-Physical Attacks Using Game-Theoretic Models

Risk analysis : an official publication of the Society for Risk Analysis, 2015

The operation of cyber infrastructures relies on both cyber and physical components, which are subject to incidental and intentional degradations of different kinds. Within the context of network and computing infrastructures, we study the strategic interactions between an attacker and a defender using game-theoretic models that take into account both cyber and physical components. The attacker and defender optimize their individual utilities, expressed as sums of cost and system terms. First, we consider a Boolean attack-defense model, wherein the cyber and physical subinfrastructures may be attacked and reinforced as individual units. Second, we consider a component attack-defense model wherein their components may be attacked and defended, and the infrastructure requires minimum numbers of both to function. We show that the Nash equilibrium under uniform costs in both cases is computable in polynomial time, and it provides high-level deterministic conditions for the infrastructur...

Power Grid Defense Against Malicious Cascading Failure

AAMAS-14

An adversary looking to disrupt a power grid may look to target certain substations and sources of power generation to initiate a cascading failure that maximizes the number of customers without electricity. This is particularly an important concern when the enemy has the capability to launch cyber-attacks as practical concerns (i.e. avoiding disruption of service, presence of legacy systems, etc.) may hinder security. Hence, a defender can harden the security posture at certain power stations but may lack the time and resources to do this for the entire power grid. We model a power grid as a graph and introduce the cascading failure game in which both the defender and attacker choose a subset of power stations such as to minimize (maximize) the number of consumers having access to producers of power. We formalize problems for identifying both mixed and deterministic strategies for both players, prove complexity results under a variety of different scenarios, identify tractable cases, and develop algorithms for these problems. We also perform an experimental evaluation of the model and game on a real-world power grid network. Empirically, we noted that the game favors the attacker as he benefits more from increased resources than the defender. Further, the minimax defense produces roughly the same expected payoff as an easy-to-compute deterministic load based (DLB) defense when played against a minimax attack strategy. However, DLB performs more poorly than minimax defense when faced with the attacker's best response to DLB. This is likely due to the presence of low-load yet high-payoff nodes, which we also found in our empirical analysis.

Vulnerability analysis of power systems based on cyber-attack and defense models

2018 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2018

Reliable operation of power systems is a primary challenge for the system operators. With the advancement in technology and grid automation, power systems are becoming more vulnerable to cyber-attacks. The main goal of adversaries is to take advantage of these vulnerabilities and destabilize the system. This paper describes a game-theoretic approach to attacker / defender modeling in power systems. In our models, the attacker can strategically identify the subset of substations that maximize damage when compromised. However, the defender can identify the critical subset of substations to protect in order to minimize the damage when an attacker launches a cyber-attack. The algorithms for these models are applied to the standard IEEE-14, 39, and 57 bus examples to identify the critical set of substations given an attacker and a defender budget.