Trustworthiness Management in the Internet of Things

The future Internet of Things (IoT) will be characterized by an increasing number of object-to-object interactions for the implementation of distributed applications running in smart environments. Object cooperation allows us to develop complex applications in which each node contributes one or more services. The Social IoT (SIoT) is one of the possible paradigms that is proposed to make the objects’ interactions easier by facilitating the search for services and the management of objects’ trustworthiness. In that scenario, in which the information moves from a provider to a requester node in a peer-to-peer network, Trust Management Systems (TMSs) have been developed to prevent the manipulation of data by unauthorized entities and guarantee the detection of malicious behaviour. The cornerstone of any TMS is the ability to generate a coherent evaluation of the information received. The community concentrates effort on designing complex trust techniques to increase their effectiveness; however, strong assumptions still need to be considered. First, nodes could provide the wrong services due to malicious behaviours or malfunctions and insufficient accuracy. Second, the requester nodes usually cannot evaluate the received service perfectly. In this regard, this thesis proposes an exhaustive analysis of the trustworthiness management in the IoT and SIoT. To this, in the beginning, we generate a dataset and propose a query generation model, essential to develop a first trust management model to overcome all the attacks in the literature. So, we implement several trust mechanisms and identify the importance of the overlooked assumptions in different scenarios. Then, to solve the issues, we concentrate on the generation of feedback and propose different metrics to evaluate it based on the presence or not of errors. Finally, we focus on modelling the interaction between the two figures involved in interactions, i.e. the trustor and the trustee, and on proposing guidelines to efficiently design trust management models.