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1. On the Rising Interdependency between the Power Grid, ICT Network, and E-Mobility: Modeling and Analysis

   https://doi.org/10.3390/en12101874  

   Mohamed, Ahmed Ali (May 2019, Energies)

   Boosting critical infrastructures’ (CIs) preparedness to threats, including natural disasters and manmade attacks, is a global imperative. The intrinsic dependencies and interdependencies between CIs hinder their resiliency. Moreover, the evolution of CIs is, in many cases, en routè to tighten those interdependencies. The goal of this paper is to uncover and analyze the rising interdependency between the electric power grid, information and communication technology (ICT) networks, and transportation systems that are heavily reliant on electric-power drivetrains, collectively referred to hereafter as electro-mobility (e-mobility). E-mobility includes electric vehicles (EVs) and electric railway systems. A new influence graph-based model is introduced, as a promising approach to model operational interdependencies between CIs. Each of the links of the influence graph represents the probability of failure of the sink node following a failure of the source node. A futuristic scenario has been analyzed assuming increased dependency of the power grid on ICT for monitoring and control, and high penetration levels of EVs and distributed energy resources (DERs) in an urban region. Inspecting the influence graph shows that the impact of interdependency between the power grid, the ICT network, and the transportation network, for the case study analyzed in this paper, does not lead to failures during normal operation with proper design; however, it is severe during emergency conditions since it leads to failure propagation among the three CIs. This paper sets the stage for more research on this topic, and calls for more attention to interdependency analysis. 

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2. A Framework to Evaluate PMU Networks for Resiliency Under Network Failure Conditions

   https://doi.org/10.1109/SmartGridComm52983.2022.9961035  

   Raj, Reuben Samson; Jin, Dong (October 2022, IEEE SmartGridComm, October 2022)

   Phasor Measurement Units (PMU), due to their capability for providing highly precise and time-synchronized measurements of synchrophasors, have now become indispensable in wide area monitoring of power-grid systems. Successful and reliable delivery of synchrophasor packets from the PMUs to the Phasor Data Concentrators (PDCs) and beyond, requires a backbone communication network that is robust and resilient to failures. These networks are vulnerable to a range of failures that include cyber-attacks, system or device level outages and link failures. In this paper, we present a framework to evaluate the resilience of a PMU network in the context of link failures. We model the PMU network as a connected graph and link failures as edges being removed from the graph. Our approach, inspired by model checking methods, involves exhaustively checking the reachability of PMU nodes to PDC nodes, for all possible combinations of link failures, given an expected number of links fail simultaneously. Using the IEEE 14-bus system, we illustrate the construction of the graph model and the solution design. Finally, a comparative evaluation on how adding redundant links to the network improves the Power System Observability, is performed on the IEEE 118 bus-system. 

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3. Realtime Robustification of Interdependent Networks under Cascading Attacks

   https://doi.org/10.1109/BigData.2018.8622022  

   Chen, Zhen; Tong, Hanghang; Ying, Lei (December 2018, 2018 IEEE International Conference on Big Data (Big Data))

   This paper studies the problem of robustifying an interdependent network by rewiring a small number of links in realtime during a cascading attack. Interdependent networks have been widely used to model interconnected complex systems such as a critical infrastructure network including both the power grid and the Internet. Realtime robustification of interdependent networks, therefore, has significant practical importance. This paper formulates the problem using the Markov decision process (MDP) framework. We first show the problem is NP-hard and then develop an effective and efficient greedy algorithm, named R EAL W IRE , to robustify the network in realtime. R EAL W IRE scores each link (and each node) based on the expected number of links failures resulted from the failure of the link (or the node), and rewires the links greedily according to the scores. Extensive experimental results show that R EAL W IRE outperforms other algorithms on multiple trobustness metrics. 

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4. Implementation Aspects of Smart Grids Cyber-Security Cross-Layered Framework for Critical Infrastructure Operation

   https://doi.org/10.3390/app12146868  

   Agnew, Dennis; Aljohani, Nader; Mathieu, Reynold; Boamah, Sharon; Nagaraj, Keerthiraj; McNair, Janise; Bretas, Arturo (July 2022, Applied Sciences)

   Communication networks in power systems are a major part of the smart grid paradigm. It enables and facilitates the automation of power grid operation as well as self-healing in contingencies. Such dependencies on communication networks, though, create a roam for cyber-threats. An adversary can launch an attack on the communication network, which in turn reflects on power grid operation. Attacks could be in the form of false data injection into system measurements, flooding the communication channels with unnecessary data, or intercepting messages. Using machine learning-based processing on data gathered from communication networks and the power grid is a promising solution for detecting cyber threats. In this paper, a co-simulation of cyber-security for cross-layer strategy is presented. The advantage of such a framework is the augmentation of valuable data that enhances the detection as well as identification of anomalies in the operation of the power grid. The framework is implemented on the IEEE 118-bus system. The system is constructed in Mininet to simulate a communication network and obtain data for analysis. A distributed three controller software-defined networking (SDN) framework is proposed that utilizes the Open Network Operating System (ONOS) cluster. According to the findings of our suggested architecture, it outperforms a single SDN controller framework by a factor of more than ten times the throughput. This provides for a higher flow of data throughout the network while decreasing congestion caused by a single controller’s processing restrictions. Furthermore, our CECD-AS approach outperforms state-of-the-art physics and machine learning-based techniques in terms of attack classification. The performance of the framework is investigated under various types of communication attacks. 

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5. A Spectral Measure for Network Robustness: Assessment, Design, and Evolution

   https://doi.org/10.1109/ICKG55886.2022.00020  

   Jin, Shengmin; Ma, Rui; Li, Jiayu; Eftekharnejad, Sara; Zafarani, Reza (November 2022, 2022 IEEE International Conference on Knowledge Graph (ICKG))

   A robust system should perform well under random failures or targeted attacks, and networks have been widely used to model the underlying structure of complex systems such as communication, infrastructure, and transportation networks. Hence, network robustness becomes critical to understanding system robustness. In this paper, we propose a spectral measure for network robustness: the second spectral moment m2 of the network. Our results show that a smaller second spectral moment m2 indicates a more robust network. We demonstrate both theoretically and with extensive empirical studies that the second spectral moment can help (1) capture various traditional measures of network robustness; (2) assess the robustness of networks; (3) design networks with controlled robustness; and (4) study how complex networked systems (e.g., power systems) behave under cascading failures. 

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