Short survey on physical layer authentication by machine-learning for 5g-based internet of things

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

5G-based Internet of Things (IoT) comprises numerous devices communicating with 10 Gbit/s peak data rate and 1 ms latency. It is challenging to secure the 5G-based IoT. Physical layer security (PLS) schemes depend on unique physical layer characteristics. They are lightweight, unconditionally securing, and thus suitable for the 5G-based IoT. This paper reviews state-of-the-art physical layer authentication (PLA) schemes using machine learning for the 5G-based IoT. The schemes are detailed and their properties are compared. Research directions of applying machine learning techniques to secure the 5G-based IoT are also pointed out in this paper.

Original languageEnglish
Title of host publicationProceedings of the 3rd IEEE International Conference on Knowledge Innovation and Invention 2020, ICKII 2020
EditorsTeen-Hang Meen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages41-44
Number of pages4
ISBN (Electronic)9781728193335
DOIs
StatePublished - 21 Aug 2020
Event3rd IEEE International Conference on Knowledge Innovation and Invention, ICKII 2020 - Kaohsiung, Taiwan
Duration: 21 Aug 202023 Aug 2020

Publication series

NameProceedings of the 3rd IEEE International Conference on Knowledge Innovation and Invention 2020, ICKII 2020

Conference

Conference3rd IEEE International Conference on Knowledge Innovation and Invention, ICKII 2020
Country/TerritoryTaiwan
CityKaohsiung
Period21/08/2023/08/20

Keywords

  • 5G
  • Internet of Things
  • Machine learning
  • Physical layer authentication

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