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Rapid popularity of Internet of Things (IoT) and cloud computing permitsneuroscientists to collect multilevel and multichannel brain data to betterunderstand brain functions, diagnose diseases, and devise treatments. To ensuresecure and reliable data communication between end-to-end (E2E) devicessupported by current IoT and cloud infrastructure, trust management is neededat the IoT and user ends. This paper introduces a Neuro-Fuzzy basedBrain-inspired trust management model (TMM) to secure IoT devices and relaynodes, and to ensure data reliability. The proposed TMM utilizes nodebehavioral trust and data trust estimated using Adaptive Neuro-Fuzzy InferenceSystem and weighted-additive methods respectively to assess the nodestrustworthiness. In contrast to the existing fuzzy based TMMs, the NS2simulation results confirm the robustness and accuracy of the proposed TMM inidentifying malicious nodes in the communication network. With the growingusage of cloud based IoT frameworks in Neuroscience research, integrating theproposed TMM into the existing infrastructure will assure secure and reliabledata communication among the E2E devices.

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