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Sensors data collection framework using mobile identification with secure data sharing model

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 9 No. 5 (2019)

DOI
10.11591/ijece.v9i5.pp4258-4265
ISSN
2722-2578, 2088-8708
Published
2019-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Sensors are the modules or electronic devices that are used to measure and get environmental events and send the captured data to other devices, usually computer processors allocated on the cloud. One of the most recent challenges is to protect and save the privacy issues of those sensors data on the cloud sharing. In this paper, sensors data collection framework is proposed using mobile identification and proxy re-encryption model for data sharing. The proposed framework includes: identity broker server, sensors managing and monitoring applications, messages queuing sever and data repository server. Finally, the experimental results show that the proposed proxy re-encryption model can work in real time.

Collaboration network of the authors

8 authors · 12 co-authorship links · 6 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • South Valley University
  • Ain Shams University
  • Jouf University
  • Al Baha University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Noha AbdElSabour SeadaAin Shams University2
Mostafa G. M. MostafaAin Shams University2
Mahmoud RashadSouth Valley University1
Kamal El-SaadySouth Valley University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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