Analysis of Cyber Security Attacks and Its Solutions for the Smart grid Using Machine Learning and Blockchain Methods

Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the most challenging things to stop. The biggest problem is caused by millions of sensors constantly sending and receivin...

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Vydané v:Future internet Ročník 15; číslo 2; s. 83
Hlavní autori: Mazhar, Tehseen, Irfan, Hafiz Muhammad, Khan, Sunawar, Haq, Inayatul, Ullah, Inam, Iqbal, Muhammad, Hamam, Habib
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.02.2023
Predmet:
Alternative energy sources
Artificial intelligence
Blockchain
Cryptography
cyber security
cyberattacks
Cybercrime
Cybersecurity
Cyberterrorism
data mining
Data security
deep learning
Electronic devices
Energy consumption
Genetic algorithms
Internet
Machine learning
Methods
Neural networks
Packets (communication)
Security software
Sensors
Smart grid
Smart sensors
ISSN:1999-5903, 1999-5903
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Shrnutí:Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the most challenging things to stop. The biggest problem is caused by millions of sensors constantly sending and receiving data packets over the network. Cyberattacks can compromise the smart grid’s dependability, availability, and privacy. Users, the communication network of smart devices and sensors, and network administrators are the three layers of an innovative grid network vulnerable to cyberattacks. In this study, we look at the many risks and flaws that can affect the safety of critical, innovative grid network components. Then, to protect against these dangers, we offer security solutions using different methods. We also provide recommendations for reducing the chance that these three categories of cyberattacks may occur.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1999-5903
1999-5903
DOI:10.3390/fi15020083