A computational trust model for social IoT based on interval neutrosophic numbers.

Nowadays, the trend of evolution of connected devices, communication networks, and cloud services towards the internet of things (IoT) has facilitated the interaction between smart objects with minimal human mediation. Considering IoT, where smart objects can be clients and providers of services for each other, trust between objects is a significant concern for selecting the most appropriate service providers. Trust is an uncertain concept, and its uncertainty originates from different sources, including context conditions, social relationships, and the accuracy of quantitative evaluations. Modeling and considering uncertainty in trust management for the IoT is the principal objective of this research. To this aim, several sources of uncertainty are modeled in trust calculations where interval neutrosophic numbers are used for modeling imprecision, indeterminacy, and inconsistency of the trustworthiness data. In the proposed model, trust in the quality of the provided services (QoS trust), as well as trust in the honesty of the socially related entities providing trust-related information (i.e. social trust), and trust in the suitability of context conditions (i.e. context-trust) are considered to calculate the overall trust used for the decision-making process. The impact of each of these dimensions on the final calculated trust has been evaluated in different scenarios. [ABSTRACT FROM AUTHOR]