Context-aware trustworthy service evaluation and recommendation in social internet of things

In Social Internet of Things (SIoT) environments, to share SIoT-based services, a large number of users and Internet of Things (IoT) based devices are connected to each other. IoT-based devices establish social relations with each other according to the social relations of their owners in Online Social Networks (OSNs). In such an environment, a big challenge is how to provide trustworthy service evaluation and recommendation. Currently, the prevalent trust management mechanisms employ QoS-based trust and social-relation based trust to evaluate the trustworthiness of service providers. However, the existing trust management mechanisms in SIoT environments do not consider the different contexts of trust. Therefore, dishonest SIoT devices, based on their owners' social relations, can succeed in advertising low-quality servicesor exploiting maliciously provided services.In this thesis, we first propose three contexts of trust in SIoT environments including statusand the environment of devices, and the task type. The experiments demonstrate that our models can select the most trustworthy services with high quality and recommend them with high accuracy to service-consuming devices.