The integration of social networking concepts into the Internet of Things (IoT) has led to the so called Social Internet of Things paradigm, according to which the objects are capable of establishing social relationships in an autonomous way with respect to their owners. Within this scenario“, things" interact opportunistically with their peers to seek needed services. However, attacks and malfunctions in the IoT can outweigh any of its benefits if not handled adequately. In this paper, we focus on the possible types of trust attacks that can affect the IoT and propose a trust management model able to overcome all the analyzed attacks. Simulations show how the proposed model can effectively isolate almost any malicious nodes in the network at the expense of an increase in the number of transactions needed for the model to converge.

Node, service and information discovery as well as trust management are key issues that characterize the IoT when huge numbers of nodes have to collaborate to support the deployed applications. A recent promising proposal, with the ability to address these issues, is the Social IoT (SIoT) paradigm, whose main principle is to enable objects to autonomously establish social links with to each other (adhering to rules set by their owners). To be able to test and validate this ability, significant datasets regarding objects' networks (node description, typology, activities, exchanged traffic) are needed, which however are not completely available. This paper addresses this issue by presenting a dataset that has been realized on the basis of real IoT objects available in the city of Santander and categorized following the typologies and data model for objects introduced in the FIWARE Data Models. Object profiles and guidelines for the relationships' creation for the SIoT are described and the obtained data and the resulting social network is made available to the research community.

Efficient energy usage inside buildings is a critical problem, particularly for high loads such as the Heating, Ventilation and Air Conditioning (HVAC) systems: over 30% of the global energy consumption resides in HVAC usage inside buildings. Usage awareness and efficient management of HVAC have the potential to significantly reduce related costs. Nevertheless, strict saving policies may contrast with users' comfort. This paper proposes a Smart HVAC system where a trade-off between energy costs and thermal comfort of users is achieved. This user-centric approach takes advantage of the Social Internet of Things (SIoT) paradigm to augment real world objects with a virtual counterpart that leverages social consciousness to interact with other objects. Accordingly, a building thermal profile is characterized to drive the selection of the most appropriate working times for the HVAC. Experimental results prove that the implemented system is able to adapt to user's needs and ensure an acceptable comfort level while at the same time reducing energy costs with reference to static or traditional scenarios.

The Social Internet of Things (SIoT) is a novel communication paradigm according to which objects connected to the Internet create a dynamic social network that is mostly used to: route information and service requests, disseminate data, and evaluate the trust level of each member of the network. The performance of these processes is clearly dependent on the following SIoT aspects: i) the structure of the social network; ii) the types of service/information requests that will mostly characterize the interaction in the IoT/SIoT; iii) the rules used to navigate the social network. This paper aims at studying these aspects through simulations as follows. The importance of each type of social relationship with respect to the navigability is observed in terms of key parameters, such as the average path length, the network diameter and size of the giant component. The concepts of nodes' geographical and similarity distances are introduced to analyse the navigability; these are then used to evaluate the performance when the communications involve objects at increasing distance. Results confirm that some types of social relationships do not appear to be useful and that the introduction of the node average distance significantly changes the resulting SIoT performance.