Power grids and their cyber infrastructure are classified as Critical Energy Infrastructure/Information (CEII) and are not publicly accessible. While realistic synthetic test cases for power systems have been developed in recent years, they often lack corresponding cyber network models. This work extends synthetic grid models by incorporating cyber-physical representations. To address the growing need for realistic and scalable models that integrate both cyber and physical layers in electric power systems, this article presents the Scalable Automatic Model Generation Tool (SAM-GT). This tool creates large-scale cyber-physical topologies for power system models. The resulting cyber-physical network models include power system switches, routers, and firewalls while accounting for dataflows and industrial communication protocols. Case studies demonstrate the tool’s application to synthetic grid models of 500, 2,000, and 10,000 buses, considering three distinct network topologies. Results from these case studies include network metrics on critical nodes, hops, and generation times, showcasing SAM-GT ’s effectiveness, adaptability, and scalability.

Modern power systems are the backbone of our society, supplying electric energy for daily activities. With the integration of communication networks and high penetration of renewable energy sources (RESs), modern power systems have evolved into a cross-domain multilayer complex system of systems with improved efficiency, controllability, and sustainability. However, increasing numbers of unexpected events, including natural disasters, extreme weather, and cyberattacks, are compromising the functionality of modern power systems and causing tremendous societal and economic losses. Resilience, a desirable property, is needed in modern power systems to ensure their capability to withstand all kinds of hazards while maintaining their functions. This article presents a systematic review of recent power system resilience enhancement techniques and proposes new directions for enhancing modern power systems’ resilience considering their cross-domain multilayer features. We first answer the question, “what is power system resilience?” from the perspectives of its definition, constituents, and categorization. It is important to recognize that power system resilience depends on two interdependent factors: network design and system operation. Following that, we present a review of articles published since 2016 that have developed innovative methodologies to improve power system resilience and categorize them into infrastructural resilience enhancement and operational resilience enhancement. We discuss their problem formulations and proposed quantifiable resilience measures, as well as point out their merits and limitations. Finally, we argue that it is paramount to leverage higher order subgraph studies and scientific machine learning (SciML) for modern power systems to capture the interdependence and interactions across heterogeneous networks and data for holistically enhancing their infrastructural and operational resilience.

For researchers studying cyber-physical system security, working with realistic datasets is essential. To produce the datasets, the existing methodology is to emulate the cyber network. A challenge is that the industrial control systems (ICS) network consists of not just computers and communication equipment, but also field devices that collect data and execute controls. These devices play a significant role in the operation and the security of the system. However, in comparison to the cyber network, the research reproducibility and realism of the cyber-physical system emulation and its data has received far less attention. This paper thus develops an approach to answer, ”How well can emulated devices replicate the behavior of physical intelligent electronics devices (IEDs) in a realistic cyber attack and defense environment?” To study this, we perform a comparison study based on an emulation experiment using theminimegatestbed environment that is entirely virtual and a hardware-in-the-loop experiment using the Resilient Energy Systems Lab (RESLab) cyber-physical testbed featuring real industrial controllers and communications devices. Results show that under different reconnaissance attack scenarios,RESLabgenerates realistic datasets that validate the emulation-based cybersecurity model inminimega. The approach is generalizable toward validating the realism of other types of ICS devices in security studies.

IP-based emergency systems (or Next Generation 9-1-1) are being designed to allow any type of communication device, from any access network, to make IP-based emergency calls. A special purpose IP network - an Emergency Services IP Network (ESINet) - is being planned by public safety agencies. In this paper, we address the challenges on defining a framework for managing the security of the signaling messages in the context of IP-based emergency calls. The challenges rely on choosing a security mechanism that protects the signaling, is practical for implementation by different parties, and meets the requirements of citizen-to-authority emergency calls.

The Location to Service Translation (LoST) protocol is a service discovery protocol, which uses location information to map service Uniform Resource Identifiers (URI). The LoST protocol was developed to support the routing process of IP-based emergency calls, known as Next Generation 9-1-1 (NG-911). In this paper, we describe testbed experiments and a new algorithm to improve the performance of the LoST protocol for mobile users. The proposed algorithm is based on the minimum distance approach to detect service boundary crossings. After comparing the minimum distance algorithm with the Ray-Tracing method, our results showed that the new algorithm considerably reduces the processing time at the mobile LoST client.

The bandwidth and reliability of the reverse link (or uplink) as the performance metrics of real-time traffic are studied in this paper. A two-level full factorial design of experiment (DOE) was conducted to identify the impact on the bandwidth and reliability of four factors: packet size, data streaming rate, time of the day, and buffer size in a real network environment. Two extreme cases for each factor were tested and statistical analysis is performed to characterize how different factors and their interactions may affect the bandwidth and reliability. The importance of this study is illustrated in the optimal channel selection mechanism where appropriate packet size, data streaming rate and buffer size can be chosen to achieve the best result.

In an integrated network in which multiple classes with different priorities exist, when the network does not have enough unused bandwidth, connection preemption algorithms (CPA) play an important role in accepting a new session with a high priority by preempting lower priority flows already admitted. Although there are lots of studies about which connections to preempt to optimize the preemption factors (the priority of connections, the bandwidth to be preempted, and the number of connections to be preempted), existing CPAs are only suboptimal from the point of view of the preemption factors because of the computational complexity. The connection preemption problem in a centralized fashion is proved to be NP-complete. To avoid the complexity of the centralized scheme, decentralized/distributed algorithms are proposed. However their solutions are optimal only at the hop level. In order to avoid the priority order problem and to minimize the number of preempted and rerouted sessions, we propose to order the priority of the preemption factors in a new way. We also propose an optimal connection preemption algorithm which optimizes the newly ordered preemption factors in the connection preemption events. The proposed algorithm is the first optimal algorithm that provides a guideline about the upper bound of the computational complexity of the optimal CPAs.

This paper presents an adaptive forward error correction (AFEC) protocol that provides a reliable communication service for real-time traffic over low-earth orbit (LEO) satellite networks. In time-varying wireless links, such as LEO satellite networks. A reliable channel estimation scheme with an appropriate code selection technique is essential for adaptive error-control systems. This paper proposes a new channel estimation scheme that uses receiver-initiated messages (ACKs, NAKs, and INCs). These messages feed back to the transmitter which then selects the code rate for sending packets. In addition, the scheme uses the concept of a dynamic transmittable code set by adjusting the maximum code rate in the set of possible codes from which the transmitter can select. In terms of throughput (from network provider's viewpoint) and packet error rate (from subscriber's viewpoint), performance results show that the proposed scheme guarantees the quality of service (QoS) requirements of real-time applications.