A survey on policies, modelling and security of cyber‐physical systems in smart grids

The modern control infrastructure that manages and monitors the communication between the smart machines represents the most effective way to increase the efficiency of the industrial environment, such as smart grids. The cyber-physical systems utilize the embedded software and internet to connect and control the smart machines that are addressed by the internet of things (IoT). These cyber-physical systems are the basis of the fourth industrial revolution which is indexed by industry 4.0. In particular, industry 4.0 relies heavily on the IoT and smart sensors such as smart energy meters. The reliability and security represent the main challenges that face the industry 4.0 implementation. This paper introduces a new infrastructure based on machine learning to analyze and monitor the output data of the smart meters to investigate if this data is real data or fake. The fake data are due to the hacking and the inefficient meters. The industrial environment affects the efficiency of the meters by temperature, humidity, and noise signals. Furthermore, the proposed infrastructure validates the amount of data loss via communication channels and the internet connection. The decision tree is utilized as an effective machine learning algorithm to carry out both regression and classification for the meters’ data. The data monitoring is carried based on the industrial digital twins’ platform. The proposed infrastructure results provide a reliable and effective industrial decision that enhances the investments in industry 4.0.

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Durchgängiges Anforderungsmanagement und Engineering für Smart Grid Lösungen

at - Automatisierungstechnik ◽

10.1515/auto-2020-0101 ◽

2020 ◽

Vol 68 (9) ◽

pp. 711-719

Author(s):

Mathias Uslar

Keyword(s):

Smart Grid ◽

Smart Grids ◽

Cyber Physical Systems ◽

Industrie 4.0 ◽

Internet Der Dinge ◽

Physical Systems

ZusammenfassungIn diesem Beitrag wird die Notwendigkeit einer sinnvollen Definition und Klarstellung der Disziplin Energieinformatik aufgezeigt. Der Beitrag diskutiert verschiedene bestehende Definitionen und stellt sie in den Kontext des Anforderungsmanagements und der Lösungsfindung. Er motiviert die Notwendigkeit eines strukturierten disziplinären Ansatzes in der Energieinformatik auf der Grundlage bestehender Probleme und skizziert den aktuellen Stand des Stands der Wissenschaft und Technik, der hauptsächlich den systemtechnischen Anwendungsbereich für Smart Grids umfasst. Synergien mit anderen aktuellen Schwerpunktthemen wie Internet der Dinge (IoT), Industrie 4.0 (Digitalisierung der Produktion) und Cyber-Physical Systems (CPS) werden aus Anforderungssicht motiviert. Auf der Grundlage der aufgeworfenen Fragen und Herausforderungen werden neue sinnvolle Forschungsthemen für ein durchgängiges Anforderungsmanagement im Kontext Smart Grid diskutiert.

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Cyber-Physical Systems Architectures and Modeling Methods Analysis for Smart Grids

2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT) ◽

10.1109/stc-csit.2018.8526726 ◽

2018 ◽

Cited By ~ 4

Author(s):

Sergiy Korotunov ◽

Galyna Tabunshchyk ◽

Carsten Wolff

Keyword(s):

Smart Grids ◽

Cyber Physical Systems ◽

Physical Systems ◽

Modeling Methods ◽

Systems Architectures

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Adoption of Machine Learning With Adaptive Approach for Securing CPS

Handbook of Research on Machine and Deep Learning Applications for Cyber Security - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-5225-9611-0.ch018 ◽

2020 ◽

pp. 388-415

Author(s):

Rama Mercy Sam Sigamani

Keyword(s):

Machine Learning ◽

Cyber Security ◽

Smart Grids ◽

False Negative ◽

False Negative Rate ◽

Cyber Physical Systems ◽

Detection Accuracy ◽

Physical Systems ◽

Positive Rate ◽

Iot Devices

The cyber physical system safety and security is the major concern on the incorporated components with interface standards, communication protocols, physical operational characteristics, and real-time sensing. The seamless integration of computational and distributed physical components with intelligent mechanisms increases the adaptability, autonomy, efficiency, functionality, reliability, safety, and usability of cyber-physical systems. In IoT-enabled cyber physical systems, cyber security is an essential challenge due to IoT devices in industrial control systems. Computational intelligence algorithms have been proposed to detect and mitigate the cyber-attacks in cyber physical systems, smart grids, power systems. The various machine learning approaches towards securing CPS is observed based on the performance metrics like detection accuracy, average classification rate, false negative rate, false positive rate, processing time per packet. A unique feature of CPS is considered through structural adaptation which facilitates a self-healing CPS.

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Smart Grids: A Cyber–Physical Systems Perspective

Proceedings of the IEEE ◽

10.1109/jproc.2015.2503119 ◽

2016 ◽

Vol 104 (5) ◽

pp. 1058-1070 ◽

Cited By ~ 221

Author(s):

Xinghuo Yu ◽

Yusheng Xue

Keyword(s):

Smart Grids ◽

Cyber Physical Systems ◽

Physical Systems ◽

Systems Perspective

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A power consensus algorithm for DC microgrids * *The work of Claudio De Persis is partially supported by NWO within the program “Uncertainty Reduction in Smart Energy Systems (URSES)” under the auspices of the project ENBARK, by the DST-NWO Indo-Dutch Cooperation on “Smart Grids” under the auspices of the project “Energy management strategies for interconnected smart microgrids” and by the STW Perspectief program “Robust Design of Cyber-physical Systems” under the auspices of the project “Energy Autonomous Smart Microgrids”. The work of Florian Dörfler is supported by ETH Zürich funds.

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2017.08.2034 ◽

2017 ◽

Vol 50 (1) ◽

pp. 10009-10014

Author(s):

Claudio De Persis ◽

Erik Weitenberg ◽

Florian Dörfler

Keyword(s):

Energy Management ◽

Smart Grids ◽

Management Strategies ◽

Energy Systems ◽

Uncertainty Reduction ◽

Cyber Physical Systems ◽

Consensus Algorithm ◽

Dc Microgrids ◽

Physical Systems ◽

Smart Energy Systems

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Distributed source coding for controlling cyber physical systems with application in smart grids

2014 IEEE Global Communications Conference ◽

10.1109/glocom.2014.7037023 ◽

2014 ◽

Author(s):

Husheng Li ◽

Zhu Han

Keyword(s):

Smart Grids ◽

Source Coding ◽

Cyber Physical Systems ◽

Distributed Source Coding ◽

Distributed Source ◽

Physical Systems

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Data driven discovery of cyber physical systems

Nature Communications ◽

10.1038/s41467-019-12490-1 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 20

Author(s):

Ye Yuan ◽

Xiuchuan Tang ◽

Wei Zhou ◽

Wei Pan ◽

Xiuting Li ◽

...

Keyword(s):

Smart Grids ◽

Underlying Mechanism ◽

Physical World ◽

Intelligent Manufacturing ◽

Cyber Physical Systems ◽

The Novel ◽

Physical Systems ◽

Embed Software ◽

Wide Range ◽

Intrinsic Complexity

Abstract Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have proved resistant to modeling due to their intrinsic complexity arising from the combination of physical and cyber components and the interaction between them. This study proposes a general framework for discovering cyber-physical systems directly from data. The framework involves the identification of physical systems as well as the inference of transition logics. It has been applied successfully to a number of real-world examples. The novel framework seeks to understand the underlying mechanism of cyber-physical systems as well as make predictions concerning their state trajectories based on the discovered models. Such information has been proven essential for the assessment of the performance of cyber-physical systems; it can potentially help debug in the implementation procedure and guide the redesign to achieve the required performance.

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A Survey of Blockchain Enabled Cyber-Physical Systems

Sensors ◽

10.3390/s20010282 ◽

2020 ◽

Vol 20 (1) ◽

pp. 282 ◽

Cited By ~ 6

Author(s):

Heena Rathore ◽

Amr Mohamed ◽

Mohsen Guizani

Keyword(s):

Data Storage ◽

Financial Services ◽

Smart Grids ◽

Health Care Systems ◽

Physical World ◽

Sharing Economy ◽

Cyber Physical Systems ◽

Digital Information ◽

Distributed Data Storage ◽

Physical Systems

Cyber-physical systems (CPS) is a setup that controls and monitors the physical world around us. The advancement of these systems needs to incorporate an unequivocal spotlight on making these systems efficient. Blockchains and their inherent combination of consensus algorithms, distributed data storage, and secure protocols can be utilized to build robustness and reliability in these systems. Blockchain is the underlying technology behind bitcoins and it provides a decentralized framework to validate transactions and ensure that they cannot be modified. By distributing the role of information validation across the network peers, blockchain eliminates the risks associated with a centralized architecture. It is the most secure validation mechanism that is efficient and enables the provision of financial services, thereby giving users more freedom and power. This upcoming technology provides internet users with the capability to create value and authenticate digital information. It has the capability to revolutionize a diverse set of business applications, ranging from sharing economy to data management and prediction markets. In this paper, we present a holistic survey of various applications of CPS where blockchain has been utilized. Smart grids, health-care systems, and industrial production processes are some of the many applications that can benefit from the blockchain technology and will be discussed in the paper.

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