Machine Learning Benchmarking for Secured IoT Smart Systems

Mohamed S. Abdalzaher, Mahmoud M. Salim, Hussein A. Elsayed, Mostafa M. Fouda

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

21 Scopus citations

Abstract

Smartness and IoT along with machine learning (ML) lead the research directions nowadays. Smart city, smart campus, smart home, smart vehicle, etc; or if we call it 'Smart x' will change how the world entities interact among themselves. This paper provides an ML benchmarking as well as a taxonomy that divides its models into linear and non-linear ones based on the problem type (classification or regression), the targeted security issue, the kind of IoT network, and the used evaluation measure. On the other hand, security algorithms enhanced with ML play a significant role to govern the new era of communication. This paper also provides a case study to apply the ML methods to IoT smart campus (SC) as a model to reach a secured IoT system for data collection and manipulation with guided research directions.

Original languageEnglish
Title of host publicationProceedings of the 2022 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages50-56
Number of pages7
ISBN (Electronic)9798350396454
DOIs
StatePublished - 2022
Externally publishedYes
Event2022 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2022 - Virtual, Online, Indonesia
Duration: 24 Nov 202226 Nov 2022

Publication series

NameProceedings of the 2022 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2022

Conference

Conference2022 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2022
Country/TerritoryIndonesia
CityVirtual, Online
Period24/11/2226/11/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • internet of things
  • Machine learning
  • security
  • smart systems

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Modeling and Simulation
  • Artificial Intelligence

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