Trust framework for handling communication using social networks as applied to mobile sensor based indoor navigation system

A research project currently being undertaken at Curtin University, proposes security aware indoor navigation system, which construct maps for use in mobility and navigation for people with vision impairments. Current effort in developing indoor navigation system using mobile sensor data requires using social network and related communication. Social Networks control considerable amount of information flow in present day networks. Social Networking sites make relationships among people and other social entities while formulating online communities. Information systems and Information Systems related projects in the enterprise uses social networks for information related communication, which presents a great risk. This paper proposed a trust-based system which process social network information and models it into a trust network. By extracting corresponding trust-related parameters of social network data, a network structure has been implemented. Afterwards a Bayesian Belief Network (BBN) was constructed. The system was evaluated by performing a personal recommendation survey. Trusted Network filter as well as the Most Un-trusted Nodes filter plugin was utilized in the evaluation process to assess real Facebook data. Results show that the system has a high accuracy. The main limitation identified is that `human factors´ could not be measured through such a computerized system, which is a key factor that affects `Trust´.