Volume 27 , Issue 1 , PP: 176-192, 2026 | Cite this article as | XML | Html | PDF | Full Length Article
Remya P. George 1 , Nazia Ahmad 2 , Rubina Liyakat Khan 3 , Sajithunisa Hussain 4 , Samandarboy Sulaymanov 5 , Ambuj Kumar Agarwal 6 *
Doi: https://doi.org/10.54216/IJNS.270117
A vast amount of Internet of Things (IoT) devices deployment has created huge issues about trust management and reliability guarantees in heterogeneous, dynamic and often uncertain ecosystems. Available probabilistic or fuzzy-logic-based models do not hold water to deal with indeterminacy and contending data in distributed IoT networks. The current paper proposes a brand new framework to model trust and reliability in IoT systems by implementing Neutrosophic Logic to build quantification and strengthen trust and reliability in IoT systems. Incorporating the semantic understanding of data and node behavior in uncertainty using three dissimilar elements to represent trust: truth, indeterminacy and falsity, the model commands a wider range of semantics in the relationship of data and nodes during the phase of uncertainty. A mathematical solution is established to measure trust scores and reliability indexes based on Neutrosophic membership functions. Further, a new dynamic trust assessment and anomaly detection algorithm is presented based on a multi-layered decision-making process. This simulation and case- study definition shows the effectiveness of the proposed framework in having less false positives, better reliability estimation, and the solid optimization of decision support in a very uncertain environment of IoT. The work therefore further develops the process of Neutrosophic systems integration with IoT and its setting up of basis of more intelligent, context-aware and robust trust management systems.
Neutrosophic Logic , internet of things (IoT) , Trust management , Reliability modeling , Indeterminacy , Uncertainty quantification , Mathematical modeling , Decision support systems
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