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A Brain-Inspired Trust Management Model to Assure Security in a Cloud Based IoT Framework for Neuroscience Applications
journal contribution
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 HussainRapid 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
10Issue number
5Page range
864-873Publication title
Cognitive ComputationISSN
1866-9964External DOI
Publisher
SpringerFile version
- Accepted version
Language
- eng
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Legacy posted date
2018-02-26Legacy creation date
2018-02-12Legacy Faculty/School/Department
ARCHIVED Faculty of Science & Technology (until September 2018)Usage metrics
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