Intelligent data attacks against power systems using incomplete network information: a review

Song, Yufei; Liu, Xuan; Li, Zhiyi; Shahidehpour, Mohammad; Li, Zuyi

doi:10.1007/s40565-018-0427-z

Cited by 25 publications

(8 citation statements)

References 50 publications

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“…Therefore, to avoid false alarms due to physical anomalies, an anomaly classification procedure is necessary for developing cybersecurity solutions. While a substantial body of literature is devoted to address the cyber-physical security of power grids [43]- [46], the deployment of cyber-physical security solutions in realworld power systems is still in a nascent stage. Recently, the dynamic watermarking method [47] has been used to detect malicious attacks on the sensors in prototypical microgrids [34], and tested via simulation on attacks on the AGC loop [41] (See Figure 8).…”

Section: B Cyber-physical Security Of Control Loopsmentioning

confidence: 99%

On an Information and Control Architecture for Future Electric Energy Systems

Xie¹,

Huang²,

Kumar³

et al. 2022

Preprint

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This paper presents considerations towards a control architecture for future electric energy systems driven by massive changes resulting from the societal goals of decarbonization and electrification. A historical perspective is provided on the role that architecture and abstractions have played in other technological systems such as the Internet, serial computation, and communication systems. For power systems, we present a viewpoint of architecture as the organization of multiple control loops aligned with the entities involved, as well as taking advantage of time-scale and spatial scale separations. New requirements and challenges in designing the set of control loops required for future electric energy systems are substantiated from a temporal and spatial scale perspective. Finally, we articulate key desirable control loops that can enable decarbonization of the electricity sector. We thereby argue that the present architecture of electric power grids designed in a different era is indeed extensible to allow the incorporation of increased renewables.

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Section: B Cyber-physical Security Of Control Loopsmentioning

confidence: 99%

On an Information and Control Architecture for Future Electric Energy Systems

Xie¹,

Huang²,

Kumar³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…If a DC model is assumed, as seen, no disclosure resources are needed. Recent works proceed by relaxing/removing the strong assumptions, first of all, that of perfect knowledge of system-wide information and parameters (see, e.g., surveys [47,48]). In [49], only full knowledge in a limited attack region is assumed, and a bi-level SE-FDIA model for causing physical disruption (line overloading) is discussed.…”

Section: Attack Design Under Reduced Assumptions Pmu Measurements and Ac Modelsmentioning

confidence: 99%

Review of Cyber-Physical Attacks in Smart Grids: A System-Theoretic Perspective

2021

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This paper presents a review of technical works in the field of cyber-physical attacks on the smart grid. The paper starts by discussing two reference mathematical frameworks proposed in the literature to model a smart grid under attack. Then, a review of cyber-physical attacks on the smart grid is presented, starting from works on false data injection attacks against state estimation. The aim is to present a systematic and quantitative discussion of the basic working principles of the attacks, also in terms of the inner smart grid vulnerabilities and dynamical properties exploited by the attack. The main contribution of the paper is the attempt to provide a unifying view, highlighting the fundamental aspects and the common working principles shared by the attack models, even when targeting different subsystems of the smart grid.

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“…To reduce NTL, power supply companies need to take the necessary measures to detect electricity theft behaviors. However, the traditional means need expensive manpower in the on-the-spot inspection of electricity meters of consumers, and only a small part of electricity theft cases can be detected successfully [4].…”

Section: Introductionmentioning

confidence: 99%

Electricity Theft Detection Based on Stacked Autoencoder and the Undersampling and Resampling Based Random Forest Algorithm

et al. 2021

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Electricity theft has been a major concern to the secure operation of power systems and the interests of power companies. Due to the different methods and types of electricity theft behaviors, it is difficult to determine the suspicion levels of consumers in the research of electricity theft detection. An electricity theft detection method based on stacked autoencoder (SAE) and the undersampling and resampling based random forest (UaRe-RF) algorithm is proposed in this work to formulate appropriate strategies for the practical electricity theft detection requirements of the power company. In the proposed method, the supervised SAE is first trained to extract electricity consumption features that are more adaptable to the classification algorithm for electricity theft detection. Then, the UaRe-RF algorithm is used to establish the class-balanced subsets and determine the suspicion level of each electricity theft user. Finally, two cases of different datasets of electricity consumers are studied for demonstrating the effectiveness of the proposed method, and the results show that higher classification accuracy and more targeted detection strategies can be achieved through the proposed method.

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Intelligent data attacks against power systems using incomplete network information: a review

Cited by 25 publications

References 50 publications

On an Information and Control Architecture for Future Electric Energy Systems

On an Information and Control Architecture for Future Electric Energy Systems

Review of Cyber-Physical Attacks in Smart Grids: A System-Theoretic Perspective

Electricity Theft Detection Based on Stacked Autoencoder and the Undersampling and Resampling Based Random Forest Algorithm

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