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Securing Smart Grid Cyber-Physical Infrastructure against Emerging Threats
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Securing Smart Grid Cyber-Physical Infrastructure against Emerging Threats

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 17977

Special Issue Editors

Dr. Daisuke Mashima

E-Mail Website
Guest Editor
Illinois at Singapore Pte Ltd., Advanced Digital Sciences Center, Singapore, Singapore
Interests: cyber-physical systems security; smart grid; privacy
Special Issues, Collections and Topics in MDPI journals
Dr. Subhash Lakshminarayana

E-Mail Website
Guest Editor
School of Engineering, University of Warwick, UK
Interests: Smart grid security, Critical infrastructure security, wireless communication
Dr. Prosanta Gope

E-Mail Website
Guest Editor
Department of Computer Science, University of Sheffield, Sheffield S1 4DP, UK
Interests: cyber security; smart grid security; wireless sensor networks and IoT security
Special Issues, Collections and Topics in MDPI journals
Dr. Neetesh Saxena

E-Mail Website
Guest Editor
School of Computer Science and Informatics, Cardiff University, Queen's Buildings, 5 The Parade, Newport Road, Cardiff CF24 3AA, UK
Interests: cyber security; cellular communication; human-centric security; Internet of Things; smart grid security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Traditionally, SCADA (supervisory control and data acquisition) infrastructure, used for remotely controlling and monitoring power grid systems, has been considered free from cybersecurity risks mainly because of the “airgap” that isolates the system infrastructure from the rest of the world. However, real-world incidents, such as Stuxnet and Ukraine power plant attacks, demonstrated that such security assumptions and models that assume the control centers are fully trusted no longer hold. Defence of our critical smart grid infrastructure against emerging cyber and cyber-physical attacks poses unique challenges, such as difficulty in modifying/upgrading devices and infrastructure, resource constraints, legacy compatibility, and stringent latency constraints, which would make application of established cybersecurity solutions for enterprise IT systems etc. difficult or less effective. The main aim of this special issue is to attract state-of-the-art, practical, cyber-physical security solutions specifically designed to address challenges in the smart grid systems. The topics of interest include, but are not limited to, the following:

  • Cross-domain, cyber-physical intrusion/anomaly detection systems for smart grid
  • AI/Machine learning application for smart grid security and resilience
  • Cryptography and key management for smart grid
  • Context-aware command authentication/validation in smart grid
  • Deception technologies and moving-target defence for smart grid
  • Design and implementation of smart grid security testbed and cyber range
  • Internet of Things for security smart grid
  • Blockchain application for smart grid (e.g., energy trading)
  • Cloud security for smart grid
  • Security and privacy in energy Internet
  • Secure, privacy-aware demand response
  • Threat intelligence collection and analysis
  • False data injection attacks and mitigation techniques

Dr. Daisuke Mashima
Dr. Subhash Lakshminarayana
Dr. Prosanta Gope
Dr. Neetesh Saxena
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Cyber-physical systems security
  • smart grid
  • industrial control systems
  • IoT

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Published Papers (4 papers)

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Research

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18 pages, 1692 KiB  
Article
DDoS Cyber-Incident Detection in Smart Grids
by Jorge C. Merlino, Mohammed Asiri and Neetesh Saxena
Sustainability 2022, 14(5), 2730; https://doi.org/10.3390/su14052730 - 25 Feb 2022
Cited by 7 | Viewed by 3708
Abstract
The smart grid (SG) offers potential benefits for utilities, electric generators, and customers alike. However, the prevalence of cyber-attacks targeting the SG emphasizes its dark side. In particular, distributed denial-of-service (DDoS) attacks can affect the communication of different devices, interrupting the SG’s operation. [...] Read more.
The smart grid (SG) offers potential benefits for utilities, electric generators, and customers alike. However, the prevalence of cyber-attacks targeting the SG emphasizes its dark side. In particular, distributed denial-of-service (DDoS) attacks can affect the communication of different devices, interrupting the SG’s operation. This could have profound implications for the power system, including area blackouts. The problem is that few operational technology tools provide reflective DDoS protection. Furthermore, such tools often fail to classify the types of attacks that have occurred. Defensive capabilities are necessary to identify the footprints of attacks in a timely manner, as they occur, and to make these systems sustainable for delivery of the services as expected. To meet this need for defensive capabilities, we developed a situational awareness tool to detect system compromise by monitoring the indicators of compromise (IOCs) of amplification DDoS attacks. We achieved this aim by finding IOCs and exploring attack footprints to understand the nature of such attacks and their cyber behavior. Finally, an evaluation of our approach against a real dataset of DDoS attack instances indicated that our tool can distinguish and detect different types of amplification DDoS attacks. Full article
(This article belongs to the Special Issue Securing Smart Grid Cyber-Physical Infrastructure against Emerging Threats)
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14 pages, 470 KiB  
Article
Application of Physics-Informed Machine Learning Techniques for Power Grid Parameter Estimation
by Subhash Lakshminarayana, Saurav Sthapit and Carsten Maple
Sustainability 2022, 14(4), 2051; https://doi.org/10.3390/su14042051 - 11 Feb 2022
Cited by 10 | Viewed by 3894
Abstract
Power grid parameter estimation involves the estimation of unknown parameters, such as the inertia and damping coefficients, from the observed dynamics. In this work, we present physics-informed machine learning algorithms for the power system parameter estimation problem. First, we propose a novel algorithm [...] Read more.
Power grid parameter estimation involves the estimation of unknown parameters, such as the inertia and damping coefficients, from the observed dynamics. In this work, we present physics-informed machine learning algorithms for the power system parameter estimation problem. First, we propose a novel algorithm to solve the parameter estimation based on the Sparse Identification of Nonlinear Dynamics (SINDy) approach, which uses sparse regression to infer the parameters that best describe the observed data. We then compare its performance against another benchmark algorithm, namely, the physics-informed neural networks (PINN) approach applied to parameter estimation. We perform extensive simulations on IEEE bus systems to examine the performance of the aforementioned algorithms. Our results show that the SINDy algorithm outperforms the PINN algorithm in estimating the power grid parameters over a wide range of system parameters (including high and low inertia systems) and power grid architectures. Particularly, in case of the slow dynamics system, the proposed SINDy algorithms outperforms the PINN algorithm, which struggles to accurately determine the parameters. Moreover, it is extremely efficient computationally and so takes significantly less time than the PINN algorithm, thus making it suitable for real-time parameter estimation. Furthermore, we present an extension of the SINDy algorithm to a scenario where the operator does not have the exact knowledge of the underlying system model. We also present a decentralised implementation of the SINDy algorithm which only requires limited information exchange between the neighbouring nodes of a power grid. Full article
(This article belongs to the Special Issue Securing Smart Grid Cyber-Physical Infrastructure against Emerging Threats)
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13 pages, 1919 KiB  
Article
MITRE ATT&CK Based Evaluation on In-Network Deception Technology for Modernized Electrical Substation Systems
by Daisuke Mashima
Sustainability 2022, 14(3), 1256; https://doi.org/10.3390/su14031256 - 23 Jan 2022
Cited by 6 | Viewed by 4976
Abstract
In recent years, cyber attacks against critical infrastructure have been increasing and are becoming stealthy and persistent. Attackers or malware may be hiding in the system after penetration to collect system information. They would further make lateral and vertical movement to seek target [...] Read more.
In recent years, cyber attacks against critical infrastructure have been increasing and are becoming stealthy and persistent. Attackers or malware may be hiding in the system after penetration to collect system information. They would further make lateral and vertical movement to seek target devices under the radar of existing cybersecurity measures. In order to counter such emerging attack vectors, in-network deception technology is attracting attention. In-network deception technology utilizes an apparently real but dummy (often virtual) devices deployed throughout the infrastructure to capture the attackers’ reconnaissance activities. In this paper, we pick one concrete design and implementation of in-network deception technology for IEC 61850 standard compliant smart substation systems in smart grid, named DecIED, and discuss its effectiveness in countering high-profile attacks that were recently witnessed in the real world. The evaluation is conducted based on the MITRE ATT&CK Matrix for industrial control systems, which tabulates phases and tactics of cyberattack against industrial control systems. Full article
(This article belongs to the Special Issue Securing Smart Grid Cyber-Physical Infrastructure against Emerging Threats)
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Review

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36 pages, 21428 KiB  
Review
A Critical Review of IEC 61850 Testing Tools
by Taha Selim Ustun
Sustainability 2021, 13(11), 6213; https://doi.org/10.3390/su13116213 - 31 May 2021
Cited by 4 | Viewed by 3873
Abstract
Smartgrid technologies necessitate the use of information technologies (IT) and communication in power system networks. There are different ways of integrating power system equipment in the communication layer for successful information exchange. IEC 61850 offers standard support object-oriented modeling and standardized parameter declaration. [...] Read more.
Smartgrid technologies necessitate the use of information technologies (IT) and communication in power system networks. There are different ways of integrating power system equipment in the communication layer for successful information exchange. IEC 61850 offers standard support object-oriented modeling and standardized parameter declaration. This lends itself to the diverse nature of power systems and supports plug-and-play (PnP) operation in smartgrids. Considering the amount of time that is invested in customizing non-PnP communication networks, this is a huge advantage and the main reason behind the popularity of IEC 61850. In line with this popularity, the body of research regarding this standard is constantly growing. In order to test the developed IEC 61850 models and messages, various tools are required. Researchers operate with a limited budget and have to know the abilities and limitations of such tools before making a procurement decision. This paper provides a critical review of IEC 61850 testing tools available in the market. It compares them in terms of their abilities, technical superiority and customer experience, including delivery time and customer support. Researchers in this field will benefit significantly from this work when making procurement decisions based on their needs. Full article
(This article belongs to the Special Issue Securing Smart Grid Cyber-Physical Infrastructure against Emerging Threats)
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