Defending false data injection attack on smart grid network using adaptive CUSUM test

Huang, Yi; Li, Husheng; Campbell, Kristy A.; Han, Zhu

doi:10.1109/ciss.2011.5766111

Cited by 93 publications

(66 citation statements)

References 11 publications

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“…In addition, as the use of phasor measurement units (PMUs) is growing, strategic allocation of secure PMUs for protection against data attacks has been also studied [12,21,27]. To facilitate fast detection of an attack, the attack detection as a quickest detection problem was also studied in [9,14,15]. The security measures will be reviewed in Section 6.…”

Section: Related Workmentioning

confidence: 99%

Against Data Attacks on Smart Grid Operations: Attack Mechanisms and Security Measures

Kim

Tong

2015

Cyber Physical Systems Approach to Smart Electric Power Grid

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Abstract. This chapter provides a survey and some highlights of recent developments on cyber security issues related to smart grid operations. In particular, we present data attack models and attack mechanisms on system state estimation, generation dispatch, and market operations. Security measures via sensor protection and data authentication are discussed. Although presented in the context of a smart grid, the main ideas are applicable to general cyber physical systems.

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Section: Related Workmentioning

confidence: 99%

Against Data Attacks on Smart Grid Operations: Attack Mechanisms and Security Measures

Kim

Tong

2015

Cyber Physical Systems Approach to Smart Electric Power Grid

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“…in [51], show that even without prior knowledge of the power grid's topology an adversary can still successfully launch stealthy bad data injection attacks. Specifically the authors prove that when the system dynamics are small and can be approximated linearly, an independent component analysis can be applied to calculate the Jacobian matrix that if multiplied by the eigenvectors of the covariance matrix of the state variables can expose information necessary to the adversary wishing to launch an unobservable false data injection attack.…”

Section: ) Ensuring Integritymentioning

confidence: 99%

Survey in Smart Grid and Smart Home Security: Issues, Challenges and Countermeasures

Komninos

Philippou²,

Pitsillides³

2014

IEEE Commun. Surv. Tutorials

506

227

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This is the unspecified version of the paper.This version of the publication may differ from the final published version. Permanent repository link:http://openaccess.city.ac.uk/3734/ Link to published version: http://dx.doi.org/10.1109/ COMST.2014.2320093 Copyright and reuse: City Research Online aims to make research outputs of City, University of London available to a wider audience. Copyright and Moral Rights remain with the author(s) and/or copyright holders. URLs from City Research Online may be freely distributed and linked to. City Research Online: http://openaccess.city.ac.uk/ publications@city.ac.ukCity Research Online  Abstract-The electricity industry is now at the verge of a new era. An era that promises, through the evolution of the existing electrical grids to Smart Grids, more efficient and effective power management, better reliability, reduced production costs and more environmentally friendly energy generation. Numerous initiatives across the globe, led by both industry and academia, reflect the mounting interest around the enormous benefits but also the great risks introduced by this evolution. This paper focuses on issues related to the security of the Smart Grid and the Smart Home, which we present as an integral part of the Smart Grid. Based on several scenarios we aim to present some of the most representative threats to the Smart Home / Smart Grid environment. The threats detected are categorized according to specific security goals set for the Smart Home/Smart Grid environment and their impact on the overall system security is evaluated. A review of contemporary literature is then conducted with the aim of presenting promising security countermeasures with respect to the identified specific security goals for each presented scenario. An effort to shed light on open issues and future research directions concludes the paper. Index Terms-Smart Grids, Smart Homes, Security, Countermeasures, Challenges I. INTRODUCTIONThe electric power infrastructure as we know it today has managed to serve our needs successfully, almost unchanged, for nearly a century; revolutionizing almost every aspect of our lives. However, as this infrastructure is inevitably aging it becomes increasingly less efficient, repeatedly running up against its limitations and constantly straining to keep up with our ever-increasing requirements. Needs for reliability, scalability, manageability, environmentally friendly energy generation, interoperability and cost effectiveness, bring forward the necessity for a modernized and intelligent grid for tomorrow; a new, reliable, efficient, flexible and secure energy infrastructure, known as the Smart Grid [1].Through the incorporation of advanced power system electronics, networking and communication technologies the Smart Grid is envisioned to significantly enhance the existing electric grid. Allowing for more accurate real-time monitoring, ensuring the optimization of power flows and enabling for two-way communication between the utility and customer sides while pointing th...

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“…By inspecting (18) and evaluating (11)- (12), we notice that the computation of the inverse Fisher information matrix can be simplified and equivalent to the covariance of residual. Based on (12), we can write the binary hypothesis {H 0 , H 1 } by expanding the multivariate normal distributions.…”

Section: Adaptive Cusum Algorithmmentioning

confidence: 99%

“…The proposed scheme is able to determine the existence of adversary as quickly as possible without violating the given constraints such as a certain level of detection accuracy in terms of the false alarm rate and missed detection rate. In [18], we studied some preliminary works that includes the basic mathematic derivation and numerical simulations; without loss of generality, one in conference version is motivated on the straightforward approach via directly evaluating the likelihood of load for detection decision, instead of formulating the algorithm based on the likelihood of residual in this paper, i.e., state estimation in power systems is based on measurement of residual, and therefore, the derivation and result from this journal can be more accurate and practical for real world applications. In additions, the conference one measured a limited range of the unknown via utilizing oneside Rao test for simplicity, while this paper considers the quadratic equivalence of Rao test for solving the unknown.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Detection of False Data Injection in Smart Grid Networks: An Adaptive CUSUM Method and Analysis

Huang

Tang

Cheng

et al. 2016

IEEE Systems Journal

Self Cite

152

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Abstract-Smart grid is delay-sensitive and requires the techniques that can identify and react on the abnormal changes (i.e. system fault, attacker, shortcut, etc.) in a timely manner. In this paper, we propose a real-time detection scheme against false data injection attack in smart grid networks. Unlike the classical detection test, the proposed algorithm is able to tackle the unknown parameters with low complexity and process multiple measurements at once, leading to a shorter decision time and better detection accuracy. The objective is to detect of adversary as quickly as possible while satisfy certain detection error constraints. A Markov chain based analytical model is constructed to systematically analyze the proposed scheme. With the analytical model, we are able to configure the system parameters for guaranteed performance in terms of false alarm rate, average detection delay, and missed detection ratio under a detection delay constraint. The Simulations are conducted with MATPOWER 4.0 package for different IEEE test systems.

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Defending false data injection attack on smart grid network using adaptive CUSUM test

Cited by 93 publications

References 11 publications

Against Data Attacks on Smart Grid Operations: Attack Mechanisms and Security Measures

Against Data Attacks on Smart Grid Operations: Attack Mechanisms and Security Measures

Survey in Smart Grid and Smart Home Security: Issues, Challenges and Countermeasures

Real-Time Detection of False Data Injection in Smart Grid Networks: An Adaptive CUSUM Method and Analysis

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