Parminder Singh
Service vs Protection: A Bayesian Learning Approach for Trust Provisioning in Edge of Things Environment
Singh, Parminder; Kaur, Avinash; Batth, Ranbir Singh; Aujla, Gagangeet Singh; Masud, Mehedi
Authors
Avinash Kaur
Ranbir Singh Batth
Dr Gagangeet Aujla gagangeet.s.aujla@durham.ac.uk
Associate Professor in Computer Science
Mehedi Masud
Abstract
Edge of Things (EoT) technology enables end-users participation with smart-sensors and mobile devices (such as smartphones, wearable devices) to the smart devices across the smart city. Trust management is the main challenge in EoT infrastructure to consider the trusted participants. The Quality of Service (QoS) is highly affected by malicious users with fake or altered data. In this paper, a Robust Trust Management (RTM) scheme is designed based on Bayesian learning and collaboration filtering. The proposed RTM model is regularly updated after a specific interval with the significant decay value to the current calculated scores to update the behavior changes quickly. The dynamic characteristics of edge nodes are analyzed with the new probability score mechanism from recent services’ behavior. The performance of the proposed trust management scheme is evaluated in a simulated environment. The percentage of collaboration devices are tuned as 10%, 50% and 100%. The maximum accuracy of 99.8% is achieved from the proposed RTM scheme. The experimental results demonstrate that the RTM scheme shows better performance than the existing techniques in filtering malicious behavior and accuracy.
Citation
Singh, P., Kaur, A., Batth, R. S., Aujla, G. S., & Masud, M. (2022). Service vs Protection: A Bayesian Learning Approach for Trust Provisioning in Edge of Things Environment. IEEE Internet of Things Journal, 9(22), 22061-22070. https://doi.org/10.1109/jiot.2021.3082272
Journal Article Type | Article |
---|---|
Online Publication Date | May 21, 2021 |
Publication Date | Nov 15, 2022 |
Deposit Date | Sep 10, 2021 |
Publicly Available Date | Sep 20, 2021 |
Journal | IEEE Internet of Things Journal |
Electronic ISSN | 2327-4662 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 9 |
Issue | 22 |
Pages | 22061-22070 |
DOI | https://doi.org/10.1109/jiot.2021.3082272 |
Public URL | https://durham-repository.worktribe.com/output/1250961 |
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