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Cited 7 time in webofscience Cited 9 time in scopus
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AI based energy harvesting security methods: A surveyopen access

Authors
Mohammadi, MasoumehSohn, Insoo
Issue Date
Dec-2023
Publisher
한국통신학회
Keywords
Artificial Intelligence(AI); Deep learning; Energy harvesting; Privacy; Security
Citation
ICT Express, v.9, no.6, pp 1198 - 1208
Pages
11
Indexed
SCIE
SCOPUS
KCI
Journal Title
ICT Express
Volume
9
Number
6
Start Page
1198
End Page
1208
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/20980
DOI
10.1016/j.icte.2023.06.002
ISSN
2405-9595
2405-9595
Abstract
Energy Harvesting (EH) as a power source plays a critical role in the advent of new technologies such as the Internet of Things (IoT). But, by providing power within the networks, it may be susceptible to attacks such as eavesdropping, data manipulation, or denial of service, leading to issues like leakage of confidential, sensitive information, and energy scarcity. Therefore, it is important to implement appropriate security measures to protect the data and devices that use energy harvested from ambient sources. In this paper, we present a comprehensive overview of the current and future developments of security for EH systems that used artificial intelligence(AI) approaches. Furthermore, we highlight the application of AI approaches such as machine learning (ML) and federated learning (FL) in the security of EH systems. Then, we discuss the security techniques that are used in the EH literature, including cryptography techniques, physical-layer security schemes, blockchain, and FL. Finally, we outline research challenges and prospects for developing and applying AI algorithms in the security of EH. © 2023 The Author(s)
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