Trust-Based Video Management Framework for Social Multimedia Networks

Social multimedia networks (SMNs) have attracted much attention from both academia and industry due to their impact on our daily lives. The requirements of SMN users are increasing along with time, which make the satisfaction of those requirements a very challenging process. One important challenge facing SMNs consists of their internal users that can upload and manipulate insecure, untrusted, and unauthorized contents. For this purpose, controlling and verifying content delivered to end users is becoming a highly challenging process. So far, many researchers have investigated the possibilities of implementing a trustworthy SMN. In this vein, the aim of this paper is to propose a framework that allows collaboration between humans and machines to ensure secure delivery of trusted video content over SMNs while ensuring an optimal deployment cost in the form of CPU, RAM, and storage. The key concepts beneath the proposed framework consist in assigning to each user a level of trust based on his/her history, creating an intelligent agent that decides which content can be automatically published on the network and which content should be reviewed or rejected, and checking the videos' integrity and delivery during the streaming process. Accordingly, we ensure that the trust level of the SMNs increases. Simultaneously, efficient capital expenditure and operational expenditures can be achieved.