Cyber Security of Smart Grids in the Context of Big Data and Machine Learning

Dogaru, Delia Ioana; Dumitrache, Ioan

doi:10.1109/cscs.2019.00018

Cited by 11 publications

(5 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The cyber-physical system of a smart grid integrating VRE can be made more secure using AI. Example studies have looked into utilizing neural networks to identify the point of attack and impact of cyber attacks, with the breach of consumer data privacy being identified as a significant threat [127].…”

Section: System Design Materials Monitoring Performance and Securitymentioning

confidence: 99%

Artificial Intelligence for Management of Variable Renewable Energy Systems: A Review of Current Status and Future Directions

Yousef,

Rocha-Meneses

2023

Energies

View full text Add to dashboard Cite

This review paper provides a summary of methods in which artificial intelligence (AI) techniques have been applied in the management of variable renewable energy (VRE) systems, and an outlook to future directions of research in the field. The VRE types included are namely solar, wind and marine varieties. AI techniques, and particularly machine learning (ML), have gained traction as a result of data explosion, and offer a method for integration of multimodal data for more accurate forecasting in energy applications. The VRE management aspects in which AI techniques have been applied include optimized power generation forecasting and integration of VRE into power grids, including the aspects of demand forecasting, energy storage, system optimization, performance monitoring, and cost management. Future directions of research in the applications of AI for VRE management are proposed and discussed, including the issue of data availability, types and quality, in addition to explainable artificial intelligence (XAI), quantum artificial intelligence (QAI), coupling AI with the emerging digital twins technology, and natural language processing.

show abstract

Section: System Design Materials Monitoring Performance and Securitymentioning

confidence: 99%

Artificial Intelligence for Management of Variable Renewable Energy Systems: A Review of Current Status and Future Directions

Yousef,

Rocha-Meneses

2023

Energies

View full text Add to dashboard Cite

show abstract

“…Figure 14. CNN architecture used in SG [139]. The publication's authors developed a technique for locating FDIA that uses a RNN and the Kalman filter.…”

Section: Cybersecurity Techniques In Sgs Based On DLmentioning

confidence: 99%

Enhancing Smart Grid Cybersecurity: A Comprehensive Analysis of Attacks, Defenses, and Innovative AI-Blockchain Solutions

Ghadi,

Talpur,

Mazhar

et al. 2023

Preprint

View full text Add to dashboard Cite

With the rapid expansion of the world population and economy, the need for energy has also increased. To minimize energy waste, it is crucial that energy be supplied to residences and businesses in an efficient manner. Smart Grids (SG) have the potential to decrease these power losses by improving the energy grid's efficiency. The effective integration of methods like artificial intelligence and blockchain into SGs has made it easier to predict customer preferences. Immediate analysis and comparison of the different AI and blockchain approaches is necessary in order to determine which approach is best for SGs. This study aims to know about some basic of smart grid. Furthermore, this study also looks at different types of layers and attacks on these layers and provide solutions of these attacks using AI and blockchain methods. At the end the study, also focus on open issues in this field and gives some future directions. By classifying attacks, proposing innovative defenses, and exploring AI and blockchain solutions, the study contributes to safeguarding smart grid infrastructures. Future research directions include addressing emerging attack strategies and refining technology for enhanced security.

show abstract

“…Another way to classify cyberattacks could be based on the target, such as energy, healthcare, and transportation [74,75]. Table 6 shows some services considered targets by adversaries.…”

Section: Phishingmentioning

confidence: 99%

“…This aspect increases the probability of cyberattacks on smart grid infrastructures [77]. Research focuses on preventing and overcoming cyberattacks by using machine learning techniques, such as artificial neural networks, to solve cybersecurity challenges, especially with the considerable volume of data on power systems [74].…”

Section: Phishingmentioning

confidence: 99%

An Exploratory Study of Cognitive Sciences Applied to Cybersecurity

et al. 2022

View full text Add to dashboard Cite

Cognitive security is the interception between cognitive science and artificial intelligence techniques used to protect institutions against cyberattacks. However, this field has not been addressed deeply in research. This study aims to define a Cognitive Cybersecurity Model by exploring fundamental concepts for applying cognitive sciences in cybersecurity. For achieving this, we developed exploratory research based on two steps: (1) a text mining process to identify main interest areas of research in the cybersecurity field and (2) a valuable review of the papers chosen in a systematic literature review that was carried out using PRISMA methodology. The model we propose tries to fill the gap in automatizing cognitive science without taking into account the users’ learning processes. Its definition is supported by the main findings of the literature review, as it leads to more in-depth future studies in this area.

show abstract

Cyber Security of Smart Grids in the Context of Big Data and Machine Learning

Cited by 11 publications

References 5 publications

Artificial Intelligence for Management of Variable Renewable Energy Systems: A Review of Current Status and Future Directions

Artificial Intelligence for Management of Variable Renewable Energy Systems: A Review of Current Status and Future Directions

Enhancing Smart Grid Cybersecurity: A Comprehensive Analysis of Attacks, Defenses, and Innovative AI-Blockchain Solutions

An Exploratory Study of Cognitive Sciences Applied to Cybersecurity

Contact Info

Product

Resources

About