An Analysis on the Effectiveness of Utilizing Facebook Graph Structure for Trust Management in a Social Iot Network

Abstract

The last few years have seen rapid growth in cyberspace social networking, with applications like Facebook, Twitter and many other similar social networking sites growing by leaps and bounds. Huge volumes of data, collected from social networking sites like Facebook (FB) can yield significant insights, some of which can be extremely useful in operations of cyber-physical systems (or CPS). Social IoT (or SIoT), an amalgamation of social networking techniques to IoT networks, is one of the growing research areas within CPS. SIoT offers a new and novel approach to network IoT devices, whereby IoT devices collaborate in a machine-to-machine (or M2M) social network, just like humans collaborate in a human social network, to solve a larger problem in a socially collaborative manner. While the approach of structuring IoT networks as a social network of collaborative devices enables an efficient deployment of a service network, it has its own security challenges. In a multi-vendor heterogeneous network of IoT devices, the challenge of identifying trustworthy devices (or friendly devices) is a tricky problem. In this paper, we first introduce the need for identification of trustworthy ties for operations in heterogeneous SIoT networks. We then briefly introduce the approach of using information available from human social networks to identify trustworthy device ties in SIoT networks. While the approach appears to be simple and elegant, the effectiveness of the approach is completely dependent on the reliability of data available from human social networks. The focus for the remainder of the paper is to use dataset analysis as means to measure the effectiveness of using Facebook social network graph for identification of trustworthy ties in SIoT networks. The assessment is equally useful when devising similar approaches for use in other CPS networks.