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A Brain-Inspired Trust Management Model to Assure Security in a Cloud Based IoT Framework for Neuroscience Applications

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posted on 2023-08-30, 15:08 authored by Mufti Mahmud, Md Shamim Kaiser, Md Mostafizur Rahman, Md Arifur Rahman, Antesar Shabut, Shamim Al-Mamun, Amir Hussain
Rapid popularity of Internet of Things (IoT) and cloud computing permits neuroscientists to collect multilevel and multichannel brain data to better understand brain functions, diagnose diseases, and devise treatments. To ensure secure and reliable data communication between end-to-end (E2E) devices supported by current IoT and cloud infrastructure, trust management is needed at the IoT and user ends. This paper introduces a neuro-fuzzy based brain-inspired trust management model (TMM) to secure IoT devices and relay nodes, and to ensure data reliability. The proposed TMM utilizes node behavioral trust and data trust estimated using Adaptive Neuro-Fuzzy Inference System and weighted additive methods respectively to assess the nodes trustworthiness. In contrast to the existing fuzzy based TMMs, the NS2 simulation results confirm the robustness and accuracy of the proposed TMM in identifying malicious nodes in the communication network. With the growing usage of cloud based IoT frameworks in Neuroscience research, integrating the proposed TMM into the existing infrastructure will assure secure and reliable data communication among the E2E devices.

History

Refereed

  • Yes

Volume

10

Issue number

5

Page range

864-873

Publication title

Cognitive Computation

ISSN

1866-9964

Publisher

Springer

File version

  • Accepted version

Language

  • eng

Legacy posted date

2018-02-26

Legacy creation date

2018-02-12

Legacy Faculty/School/Department

ARCHIVED Faculty of Science & Technology (until September 2018)

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