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- W4364305472 abstract "The properties and features of wireless channels have recently attracted the attention of researchers since they include valuable and powerful parameters for security services. This has paved the way for a new security paradigm, Physical Layer Security (PLS). To further improve the performance and security of such technology, it is recently being combined with machine learning algorithms to provide authentication, confidentiality and intrusion detection. Motivated by the novel advancements in this field, we present a brief overview of the different machine learning techniques and algorithms that offer PLS-based security services. These techniques are discussed in details to shed the light on the existing methods in the literature. We also propose several recommendations for enhancing the performance and efficiency of the presented schemes." @default.
- W4364305472 created "2023-04-12" @default.
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- W4364305472 date "2022-10-01" @default.
- W4364305472 modified "2023-09-25" @default.
- W4364305472 title "Machine Learning for Physical Layer Security: Limitations, Challenges and Recommendation" @default.
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- W4364305472 doi "https://doi.org/10.1109/sitis57111.2022.00017" @default.
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