Abstract

The world is transitioning from the conventional grid to the smart grid at a rapid pace. Innovation always comes with some flaws; such is the case with a smart grid. One of the major challenges in the smart grid is to protect it from potential cyberattacks. There are millions of sensors continuously sending and receiving data packets over the network, so managing such a gigantic network is the biggest challenge. Any cyberattack can damage the key elements, confidentiality, integrity, and availability of the smart grid. The overall smart grid network is comprised of customers accessing the network, communication network of the smart devices and sensors, and the people managing the network (decision makers); all three of these levels are vulnerable to cyberattacks. In this survey, we explore various threats and vulnerabilities that can affect the key elements of cybersecurity in the smart grid network and then present the security measures to avert those threats and vulnerabilities at three different levels. In addition to that, we suggest techniques to minimize the chances of cyberattack at all three levels.

Highlights

  • The conventional electricity system has been enhanced with modern technology, transforming it into a smart grid

  • The results show that autoencoder-based prediction model performance was better than long short-term memory (LSTM), random forest, naïve Bayes, decision tree, k-nearest neighbor, and LSVM

  • Employees in an organization can be categorized as attitudinal and cognitive [58] regular employees training can be helpful in combatting cyberattacks

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Summary

Introduction

The conventional electricity system has been enhanced with modern technology, transforming it into a smart grid. There are numerous benefits of the smart grid over traditional grids such as improved power quality, self-healing, cost effectiveness with the integration of renewable energy, adaptive energy generation, more environmentally friendly operation, aggregation of distributed energy resources (DERs), real-time energy consumption monitoring at customer’s end, integration of AI models to automate tasks, remote energy motoring, rapid response to faults, remote fault location identification, and automated maintenance. These benefits make the smart grid more attractive than the traditional grid.

Communication Architecture of Smart Grid
Vulnerabilities in the Smart Grid
Primary Goals of the Cybersecurity in the Smart Grid
Brief History of Cyberattacks on Smart Grids and Blackouts
Cyberattack Detection and Mitigation Techniques
Machine-Learning-Based Attack Detection and Mitigation
Continous and adaptive learning
High energy consumption to run all the nodes
Cloud-Based Detection and Mitigation
Blockchain-Based Detection and Mitigation
Hardware-Based Security
Employee Protection at Command and Control Center Technique
Customer Protection Technique
Findings
Conclusions
Full Text
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