A Deep Learning-Based Cyberattack Detection System for Transmission Protective Relays

Khaw, Yew Meng; Jahromi, Amir Abiri; Arani, Mohammadreza Fakhari Moghaddam; Sanner, Scott; Kundur, Deepa; Kassouf, Marthe

doi:10.1109/tsg.2020.3040361

Cited by 63 publications

(30 citation statements)

References 27 publications

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“…Firms showed benefits, such as an increase of productivity, and faster time responses to suppliers and consumers. RA from the Adoption of decision-making processes is more relevant for organizations in logistics, maritime (Mileski et al, 2018) and manufacturing organizations (Huma et al, 2021;Khaw et al, 2021) than for those organizations in the service industry. On a comparative note, Yeboah-Ofori et al (2021), highlighted the following sectors as cyber vulnerable: Energy, Communication, Transport, Health-care and Manufacturing, and calls on cybersecurity to include the global delivery of physical goods plus the delivery of software.…”

Section: Discussionmentioning

confidence: 99%

Eleven years of cyberattacks on Chinese supply chains in an era of cyber warfare, a review and future research agenda

Pérez-Morón

2021

JABS

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Purpose The contribution of this study aims to twofold: First, it provides an overview of the current state of research on cyberattacks on Chinese supply chains (SCs). Second, it offers a look at the Chinese Government’s approach to fighting cyberattacks on Chinese SCs and its calls for global governance. Design/methodology/approach A comprehensive literature review was conducted on Clarivate Analytics’ Web of Science, in Social Sciences Citation Index journals, Scopus and Google Scholar, published between 2010–2021. A systematic review of practitioner literature was also conducted. Findings Chinese SCs have become a matter of national security, especially in the era of cyber warfare. The risks to SC have been outlined. Cybersecurity regulations are increasing as China aims to build a robust environment for cyberspace development. Using the Technology-organization-environment (TOE) framework, the results show that the top five factors influencing the adoption process in firms are as follows: relative advantage and technological readiness (Technology context); top management support and firm size (Organization context) and government policy and regulations (Environment context). Research limitations/implications This review focuses on cyberattacks on Chinese SCs and great care was taken when selecting search terms. However, the author acknowledges that the choice of databases/terms may have excluded a few articles on cyberattacks from this review. Practical implications This review provides managerial insights for SC practitioners into how cyberattacks have the potential to disrupt the global SC network. Originality/value Past researchers proposed a taxonomic approach to evaluate progress with SC integration into Industry 4.0; in contrast, this study is one of the first steps toward an enhanced understanding of cyberattacks on Chinese SCs and their contribution to the global SC network using the TOE framework.

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Section: Discussionmentioning

confidence: 99%

Eleven years of cyberattacks on Chinese supply chains in an era of cyber warfare, a review and future research agenda

Pérez-Morón

2021

JABS

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“…Due to the hybridization approach, the additional hyperparameters dramatically decrease the model's learning efficiency [85]. In [86], an unsupervised DL scheme-based cyberattack detection system for transmission protective relays has been proposed using a 1-dimensional convolutional-based AE. A comparative study of AE and its variants is presented in Table 3.…”

Section: E Autoencodersmentioning

confidence: 99%

Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects

et al. 2021

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The current electric power system witnesses a significant transition into Smart Grids (SG) as a promising landscape for high grid reliability and efficient energy management. This ongoing transition undergoes rapid changes, requiring a plethora of advanced methodologies to process the big data generated by various units. In this context, SG stands tied very closely to Deep Learning (DL) as an emerging technology for creating a more decentralized and intelligent energy paradigm while integrating high intelligence in supervisory and operational decision-making. Motivated by the outstanding success of DL-based prediction methods, this article attempts to provide a thorough review from a broad perspective on the state-of-the-art advances of DL in SG systems. Firstly, a bibliometric analysis has been conducted to categorize this review's methodology. Further, we taxonomically delve into the mechanism behind some of the trending DL algorithms. We then showcase the DL enabling technologies in SG, such as federated learning, edge intelligence, and distributed computing. Finally, challenges and research frontiers are provided to serve as guidelines for future work in the futuristic power grid domain. This study's core objective is to foster the synergy between these two fields for decision-makers and researchers to accelerate DL's practical deployment for SG systems. INDEX TERMSSmart grid, deep learning, deep neural networks, edge computing, distributed and federated learning, power systems. NOMENCLATURE Abbreviations DDL Distributed deep learning DL Deep learning DRL Deep reinforcement learning DRN Deep residual network EI Edge intelligence EPS Electric power systems FL Federated learning IoT Internet of things LSTM Long short-term memory neural network The associate editor coordinating the review of this manuscript and approving it for publication was Shadi Alawneh . NN Neural network PVPF Photovoltaic power forecasting D. RESEARCH METHODOLOGY AND SYSTEMATIC REVIEW PROTOCOLStarting from September 2019, the multiple-methods approach was conducted [24]. The collection of the mainstream research papers on SG/AI from Web of Science (WoS), Scopus, IEEE Xplore, Science Direct, and Google scholar was conducted as the largest databases of peerreviewed articles. Only peer-reviewed articles written in English, providing experimental results, and having a unique identifier from the mentioned databases were taken into consideration, including reviews, research articles, patent reports, and conference proceedings. The adopted methodology for conducting this review article employs a combination of keywords categorized into three main groups, specifically, 'Deep Learning', 'Smart Grid', and 'Prediction'. The search methodology focuses on the recent research articles from 2015-2020 to identify the comprehensive statues of the AI applications on SG. The filtering process results in 220 research papers from 600 related papers selected based on their relevance by reading the title, abstract, conclusion,

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“…3. This attack model exploits the vulnerabilities in the IEC 61850 protocol to capture and modify, or fabricate false signals, as discussed in [36], [37]. This attack is feasible due to lack of communication encryption.…”

Section: Attack Modelmentioning

confidence: 99%

False Data Injection Attacks Against Synchronization Systems in Microgrids

Mohamed

Arani

Jahromi

et al. 2021

IEEE Trans. Smart Grid

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Synchronization systems play a vital role in the day-to-day operation of power systems and their restoration after cascading failures. Hence, their resilience to cyberattacks is imperative. In this paper, we demonstrate that a well-planned false data injection attack against the synchronization system of a generator is capable of causing tripping subsequently leading to instability and blackout. We present an analytical framework behind the design and implementation of the proposed cyberattack. Moreover, we derive and discuss the conditions for which a cyberattack interfering with a synchronizing signal can be successful. Effective physical mitigation strategies are then proposed to improve the cyber-resilience of synchronization systems. The proposed cyberattack model and mitigation strategies are verified for a microgrid test system using an OPAL-RT real-time simulator.

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A Deep Learning-Based Cyberattack Detection System for Transmission Protective Relays

Cited by 63 publications

References 27 publications

Eleven years of cyberattacks on Chinese supply chains in an era of cyber warfare, a review and future research agenda

Eleven years of cyberattacks on Chinese supply chains in an era of cyber warfare, a review and future research agenda

Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects

False Data Injection Attacks Against Synchronization Systems in Microgrids

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