Analysis of information flow security in cyber–physical systems

Guest Editorial

Synthetically analyze the power distribution communication network technology in the smart power grid link. It mainly includes the summary of the smart distribution network, electric power communication backbone network and then layer communication requirements, the network mode and the application mode of WLAN technology in the distribution network, EPON network technology, micropower wireless technology, PTN technology and power broadband wireless systems. State the demand of the smart power distribution business and put forward technical guidance for the smart power distribution communication network scheme. In view of the complex distribution network architecture, more nodes and scattered, complex business types data business needs, put forward the integrated solutions of optical fiber communication as the backbone access, wireless bandwidth, passive optical communication as the coverage, the short distance wireless communication as the main terminal access. It provides a reference for the communication plan of distribution side.

The smart grid is an upgraded concept of electricity network with tight coupling among information, control, and bi‐directional communication technologies. Along with the silent features of the on‐going smart grid, cyber–physical security appears to be a deep concern due to its significant dependence on sensing technologies, complex networks of computers, intelligence, and wide‐area communication infrastructures. Moreover, the smart grid is an extensive critical infrastructure and vulnerable to coordinated cyber–physical attacks. As a result, cyber–physical attacks cause significant threats to the confidentiality and integrity of the power data, including power outages, cascading failures, and unnecessary expenditure. In this study, security issues of smart grid, including cyber–physical interdependency, attack varieties, detection methods, requirements, standards, challenges, and future prospects, are taken into consideration for both cyber and physical systems, aiming to provide an extensive understanding of vulnerabilities and solutions for the smart power grid. By revealing the inherent features of cyber–physical security in the smart grid, this survey study is addressed to facilitate future research in these two areas.

A survey on applications of Alternating Direction Method of Multipliers in smart power grids

Smart grids are electric networks that employ advanced monitoring, control, and communication technologies to deliver reliable and secure energy supply, enhance operation efficiency for generators and distributors, and provide flexible choices for prosumers. Smart grids are a combination of complex physical network systems and cyber systems that face many technological challenges. In this paper, we will first present an overview of these challenges in the context of cyber-physical systems. We will then outline potential contributions that cyber-physical systems can make to smart grids, as well as the challenges that smart grids present to cyber-physical systems. Finally, implications of current technological advances to smart grids are outlined.

Smart grids are electric grids that utilize advanced technologies of monitoring, control, and communication to supply reliable and secure energy, improve the efficiency of the system, and provide flexibility to the prosumers. The beginning of the smart grid era and the development in modern infrastructures of metering, communication, and energy storage have revolutionized the power grid. Smart grids are developed with complex physical networks and cyber systems thus enabling smart grids for the Internet of Energy (IoE). IoE is the cloud where sources of power generation and loads of power consumption are embedded with intelligence. Modern electric power grids are integrated with sensors used to provide measurements. The sensor measurements and the complex applications of various sensors cause a need for Cyber-Physical System (CPS). CPS is a class of systems that integrates physical process, computation, and networking. The CPS model of the smart grid helps in modeling and simulation for evaluation of the system performance and characteristics. The CPS model of the smart grid must enable the smart grid to be robust, 2allow future extensions, and compatible with web service technologies. The power generation sources and loads such as smart buildings are the physical layers, the sensors used for measurements form the cyber-physical integration and the data storage and processing using IOE forms the cyber layer of the smart grid. The CPS model of the smart grid helps in the integration of intelligent devices and allied information and communication technologies for robust and reliable operation in smart grids. In the smart grid paradigm, the energy management system has a vital role to increase the efficiency and reliability of the system. This chapter presents a CPS model for smart grid and the challenges associated with the development of the CPS model. In addition, this chapter describes the energy management system model of the smart grid.

Smart grids are complex systems for which simulation offers a practical way to evaluate and compare multiple solutions before deployment. However, the simulation of a Smart Grid requires the development of heterogeneous models corresponding to electrical, information processing, and telecommunication behaviors. These heterogeneous models must be linked and analyzed together in order to detect the influences on one another and identify emerging behaviors. We apply model-driven engineering to such cyber-physical systems combining physical and digital components and propose SGridSF, the Smart Grid Simulation Framework, which automates tasks in order to ensure consistency between different simulation models. This framework consists mainly of a domain specific language for modeling a cosimulation unit, called CosiML for Cosimulation Modeling Language, a domain specific language for modeling the functional architecture of a Smart Grid, called SGridML for Smart Grid Modeling Language, and a tool implementing different transformation rules to generate the files and scripts for executing a cosimulation. Finally, we illustrate the use of SGridSF on the real use case of an islanded grid implementing diesel and renewable sources, battery storage and intelligent control of the production. We show the sequencing of automatic generation tasks that minimizes the effort and the risk of error at each iteration of the process.

Electric power grids are lagging in flexibility and time-response. A smart grid is an improved version of electrical grids that leverages Internet of Things (IoT) based devices to improve the overall infrastructure from the grid stations to intelligent appliances. It provides better understanding of supply and demand and overall flow of data depending based upon the requirements. Modern approach towards Smart grid envisions to provide electricity consumers with the opportunity to manage their respective power usage. Population increase has played a major role in the adoption of smart grid as a lot of electrical energy is consumed in the residential sector and a lot of architectures have been proposed for better flow of information from the smart meter to connectors and devices for improved customer participation. Customer needs have been very important in the smart grid. However, the customers have never been provided with the ease of choosing their own kind of benefits from the smart grid. In this work, we propose an enhanced architecture working effectively for multiple users based on their requirements. The users would be able to choose their type of scheduling techniques based on their requirements. These requirements may include cost reduction and increasing user comfort for better consumption of electricity and reliable systems. These requirements can be achieved using different Bio inspired computing based scheduling algorithms. Furthermore, in this work, we provide a comparison of these bio inspired scheduling techniques, i.e., Enhanced Differential Evolution, Bacterial Foraging Algorithm and Grey Wolf Optimization integrated in smart grid architecture for providing better consumption of electricity and achieving reliable systems. These algorithms mainly aim to schedule load, minimize electricity bills and maximize the user comfort depending on user demand.

Securing cyber-physical systems (CPS) like the Smart Grid against cyber attacks is making it imperative for the system defenders to plan for investing in the cybersecurity resources of cyber-physical critical infrastructure. Given the constraint of limited resources that can be invested in the cyber layer of the cyber-physical smart grid, optimal allocation of these resources has become a priority for the defenders of the grid. This paper proposes a methdology for optimizing the allocation of resources for the cybersecurity infrastructure in a smart grid using attack-defense trees and game theory. The proposed methodology uses attack-defense trees (ADTs) for analysing the cyber-attack paths (attacker strategies) within the grid and possible defense strategies to prevent those attacks. The attack-defense strategy space (ADSS) provides a comprehensive list of interactions between the attacker and the defender of the grid. The proposed methodology uses the ADSS from the ADT analysis for a game-theoretic formulation (GTF) of attacker-defender interaction. The GTF allows us to obtain strategies for the defender in order to optimize cybersecurity resource allocation in the smart grid. The implementation of the proposed methodology is validated using a synthetic smart grid model equipped with cyber and physical components depicting the feasibility of the methodology for real-world implementation.

Availability importance measures of components in smart electric power grid systems

Cyber-Physical Systems (CPS) are infrastructures with capabilities of perception, networking, and computation. They consist of physical and virtual components that interact with their environment. Their main goal is to monitor the physical system in real-time to have its behavior under control. Some of these infrastructures require well-defined security measures due to their critical processing capabilities. Digital Twins are defined as virtual structures emulating the physical components in various systems. They enable the deployment of isolated simulation environments to test changes and specify the security issues of a CPS. One of the main applications of CPS is smart grids. Microservices allow us to create fine-grained operations on automation systems. Using small, well-defined, modular processes, we can observe the states of smart grid infrastructure in many stages. In this work, we aim to design a framework that can create a reliable environment for smart grids compliant with existing industrial standards. We propose a service-oriented digital twins framework consisting of entities such as power meters, data aggregators, and system parameters for providing a scalable and highly available platform for complex energy systems.

The smart grid system is composed of the power infrastructure and communication infrastructure and thus is characterized by the flow of electric power and information, respectively. Although there is no doubt that the wireless communication architecture will play a significant role in smart grid, the wireless network introduces additional vulnerabilities, given the scale of potential threats. Therefore, the physical layer security issue is of first priority in the study of smart grid and has already attracted substantial attention in the industry and academia. In this paper, we aimed to present a general overview of the physical layer security in wireless smart grid and cover the effective countermeasures proposed in the literature of smart grid to date. We first investigate the security challenges from malicious attacks. Specifically, two typical forms of malicious attack in smart grid, namely, jamming and bad data injecting, are studied. In addition, the related countermeasures against these malicious attacks are illustrated. Further, we analyze the state of the art of the privacy issues in smart grid. The private information and privacy concerns are introduced, and then the effective solutions to privacy security are provided. Finally, voltage regulation, a security topic that has been hardly studied in the wireless smart grid domain, is presented. We expect that the work presented here will advance the research on smart grid security. Copyright © 2013 John Wiley & Sons, Ltd.

Cyber-physical systems (CPS) are aimed at combining the physical system with the cyber ones to provide a better control and improve the management of physical systems around us. Recently, the CPS and its applications, e.g., health-care and smart grid, have gained attention of the research community. In this paper, we consider the privacy aspect of users in a CPS, particularly in smart grid system as our use-case, and provide a mechanism that utilizes the advances in network coding to maintain data privacy. We address privacy issues associated with gathering metering information of clients in a smart grid system. In smart grid systems, wireless multi-hop communications are mainly used to gather metering information through exchanging data and control messages between smart meters and the utility. We argue that any communication paradigm used in a smart grid should support all aspects of privacy such as anonymity, unlinkability, unobservablity, and undetectablity. We propose innovative schemes for traffic routing and encryption that benefit from the enhanced network coding technology. Our analysis shows that our schemes maintain privacy of users despite the possibility of detecting metering data by an adversary. In addition, our scheme has extra favorable features such as less computation complexity, reliable, and robust communication.

Over the last decade, Internet of Things (IoTs) have brought radical changes to the means and forms of communication for monitoring and control of a large number of applications including Smart Grid (SG). Traditional energy networks have been modernized to SGs to boost the energy industry in the context of efficient and effective power management, performance, real-time control and information flow using two-way communication between utility provides and end-users. However, integrating two-way communication in SG comes at the cost of cyber security vulnerabilities and challenges. In the context of SG, node compromise is a severe security threat due to the fact that a compromised node can significantly impact the operations and security of the SG network. Therefore, in this chapter, Key Management Scheme for Communication Layer in the Smart Grid (KMS-CL-SG) has proposed. In order to achieve a secure end-to-end communication we assign a unique key to each node in the group.

Traditional electric generation based on fossil fuel consumption threatens the humanity with global warming, climate change, and increased carbon emission. Renewable resources such as wind or solar power are the solution to these problems. The smart grid is the only choice to integrate green power resources into the energy distribution system, control power usage, and balance energy load. Smart grids employ smart meters which are responsible for two-way flows of electricity information to monitor and manage the electricity consumption. In a large smart grid, smart meters produce tremendous amount of data that are hard to process, analyze and store even with cloud computing. Fog computing is an environment that offers a place for collecting, computing and storing smart meter data before transmitting them to the cloud. This environment acts as a bridge in the middle of the smart grid and the cloud. It is geographically distributed and overhauls cloud computing via additional capabilities including reduced latency, increased privacy and locality for smart grids. This study overviews fog computing in smart grids by analyzing its capabilities and issues. It presents the state-of-the-art in area, defines a fog computing based smart grid and, gives a use case scenario for the proposed model.