Machine Learning and PUF based Authentication Framework for Internet of Medical Things

Pintu Kumar Sadhu, Anik Baul, Venkata P. Yanambaka, Ahmed Abdelgawad

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

Abstract

The advancement of technology enables the connection of humans with the digital system through the Internet of Things (IoT). Likewise, the internet of medical things (IoMT), is helping patients connect to doctors using medical equipment. To maintain the integrity of sensitive data and preserve privacy, IoMT requires robust authentication mechanisms. This paper proposes a lightweight authentication framework using physical unclonable function (PUF) and machine learning (ML). The framework needs 2.33ms as computation cost and 68 bytes as communication cost. Moreover, the ML shows 99.76% accuracy.

Original languageEnglish
Title of host publication2022 International Conference on Microelectronics, ICM 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages160-163
Number of pages4
ISBN (Electronic)9781665493246
DOIs
StatePublished - 2022
Event2022 International Conference on Microelectronics, ICM 2022 - Virtual, Online, Morocco
Duration: Dec 4 2022Dec 7 2022

Publication series

Name2022 International Conference on Microelectronics, ICM 2022

Conference

Conference2022 International Conference on Microelectronics, ICM 2022
Country/TerritoryMorocco
CityVirtual, Online
Period12/4/2212/7/22

Keywords

  • Authentication System
  • Internet of Medical Things
  • Machine Learning
  • Physical Unclonable Function

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