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Applied Sciences
Special Issues
Emerging Topics on Cyber-Physical Energy Systems Security
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Emerging Topics on Cyber-Physical Energy Systems Security

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (31 May 2020) | Viewed by 3769

Special Issue Editors

Dr. Charalambos Konstantinou

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Guest Editor
1. Center for Advanced Power Systems (CAPS), Florida State University, Tallahassee, FL 32310, USA
2. Department of Electrical and Computer Engineering, FAMU-FSU College of Engineering, Tallahassee, FL 32310, USA
Interests: cyber-physical systems; cybersecurity; smart grid; power systems resilience and control
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Paras Mandal

E-Mail Website
Guest Editor
Power & Renewable Energy Systems (PRES) Lab., Department of Electrical & Computer Engineering, The University of Texas at El Paso, El Paso, TX 79968, USA
Interests: energy forecasting; cyber-physical systems; smart grid; power systems operations and control; machine learning; intelligent systems; data analytics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Motivated by concerns about safety, efficiency, performance, stability, robustness, and sustainability, several sectors, including energy, autonomous automobile systems, healthcare, avionics, and transportation, have witnessed notable advances in automation, monitoring, and control over the past few years. As a result, the integration of communication, information, and computation with physically engineered systems demands a thorough analysis of Cyber-Physical Systems (CPS) so as to realize targeted technological and economic metrics. The electric power grid is a complex CPS that forms the backbone of critical infrastructure and the lifeline of modern societies. As a result, the concept of Cyber-Physical Energy Systems (CPES) is an emerging concept bringing topics from the field of CPS and smart grid applications into the energy sector processes so as to improve the reliability, security, and efficiency of the electric grid.

The recent advents in attack modeling, threat assessment, machine learning, information theory, cryptography, and computing create a new paradigm for the security of CPES. Moreover, recent real-world attack incidents in critical CPES infrastructures underscore the huge importance of the study of CPES security. To preserve the availability and integrity of CPES, defense mechanisms related to prevention, resiliency, and detection need to be evolved, and more attention is needed from experts in industry and academia to fill the gap.

The main goal of this Special Issue is to bring together scholars, researchers, scientists, engineers, and administrators on a common platform to develop, design, and publish new ideas and concepts to improve the field security of CPES. The relevant topics include but are not limited to the following:

  • Attack and threat modeling and assessment approaches;
  • Machine learning and big data for attack and defense strategies;
  • Sensing and control for security protecting and trust management;
  • Supervisory and data acquisition systems (SCADA) and industrial control system (ICS) security;
  • Secure and trustworthy CPES;
  • Critical CPES infrastructure security and real-time assessment;
  • Intrusion detection and prevention methods;
  • Hybrid CPES security and concurrency;
  • Legacy CPES protection;
  • Embedded systems security in CPES.

Assist. Prof. Charalambos Konstantinou
Assoc. Prof. Dr. Paras Mandal
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. Applied Sciences 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.

Published Papers (2 papers)

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Research

17 pages, 3545 KiB  
Article
An Epistemic Utility-Theoretic Model in Fortifying Oil-and-Gas Production Networks
by Mustafa Alassad, Hamzeh Davarikia and Yupo Chan
Appl. Sci. 2020, 10(11), 3870; https://doi.org/10.3390/app10113870 - 02 Jun 2020
Cited by 2 | Viewed by 1520
Abstract
Oil-and-gas networks are systems of pumps and pipelines that are exposed to heterogeneous threats. Accordingly, hardening strategies against malicious attacks are needed in today’s geopolitical climate. In this paper, a tri-level leader–follower–operator game is established for determining the optimal fortification tactics to protect [...] Read more.
Oil-and-gas networks are systems of pumps and pipelines that are exposed to heterogeneous threats. Accordingly, hardening strategies against malicious attacks are needed in today’s geopolitical climate. In this paper, a tri-level leader–follower–operator game is established for determining the optimal fortification tactics to protect the critical assets considering the petroleum firm limited resources. We additionally consider defender options beyond outright fortification including tactics often adapted in the fog of war, such as deception. These are mathematically modeled under shared cognition concepts. The proposed model assumes a trial-and-error learning process to gradually discover effective defense strategies. These strategies may include a network defender projecting false information in the media or on the front lines to deceive the aggressor. The resulting mixed-integer nonlinear programming problem is decomposed into a master problem associated with deception and sub-problem as response strategies. A column-and-constraint generation solution duly takes into account the defender–operator and attacker–operator interactions. Further, linearization techniques are applied to reformulate the problem into a mixed-integer linear problem. Our studies performed on the part of the Iraq oil-and-gas network and computational results verified that the deception concept is much more effective than fortification, where the cost of attackers damages diminished significantly without substantial resources commitment on the part of the defender. Full article
(This article belongs to the Special Issue Emerging Topics on Cyber-Physical Energy Systems Security)
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32 pages, 2802 KiB  
Article
Cyber–Physical Active Distribution Networks Robustness Evaluation against Cross-Domain Cascading Failures
by Pengpeng Sun, Yunwei Dong, Chong Wang, Changchun Lv and Khursheed Yousuf War
Appl. Sci. 2019, 9(23), 5021; https://doi.org/10.3390/app9235021 - 21 Nov 2019
Cited by 3 | Viewed by 1840
Abstract
Active distribution networks (ADNs) are a typical cyber–physical system (CPS), which consist of two kinds of interdependent sub-networks: power networks (PNs) and communication networks (CNs). The combination of typical characteristics of the ADN includes (1) a large number of distributed generators contained in [...] Read more.
Active distribution networks (ADNs) are a typical cyber–physical system (CPS), which consist of two kinds of interdependent sub-networks: power networks (PNs) and communication networks (CNs). The combination of typical characteristics of the ADN includes (1) a large number of distributed generators contained in the PN, (2) load redistribution in both the PN and CN, and (3) strong interdependence between the PN and CN, which makes ADNs vulnerable to cross-domain cascading failures (CCFs). In this paper, we focus on the robustness analysis of the ADN against the CCF. Rather than via the rate of the clusters with size greater than a predefined threshold, we evaluate the robustness of the ADN using the rate of the clusters containing generators after the CCF. Firstly, a synchronous probabilistic model is derived to calculate the proportions of remaining normal operational nodes after the CCF. With this model, the propagation of the CCF in the ADN can be described as recursive equations. Secondly, we analyze the relationship between the proportions of remaining normal operational nodes after the CCF and the distribution of distributed generators, unintentional random initial failure rate, the interdependence between the sub-networks, network topology, and tolerance parameters. Some results are revealed which include (1) the more distributed generators the PN contains, the higher ADN robustness is, (2) the robustness of the ADN is negatively correlated with the unintentional random initial failure rate, (3) the robustness of the ADN can be improved by increasing the average control fan in of each node in the PN and the average power fan in of each node in the CN, (4) the robustness of the ADN with Erdos–Renyi (ER) network topological structure is greater than that with Barabasi–Albert (BA) network topological structure under the same average node degree, and (5) the robustness of the ADN is greater, when the tolerance parameters increase. Lastly, some simulation experiments are conducted and experimental results also demonstrate that the conclusions above are effective to improve the robustness of the ADN against the CCF. Full article
(This article belongs to the Special Issue Emerging Topics on Cyber-Physical Energy Systems Security)
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