A social qualitative trust framework for Fog computing

The field of Internet of Things (IoT) is evolving at an exponential rate where megabytes of data is being processed each passing minute. Fog computing is an emerging field, regarded as the new way forward to prevent the suspected data outburst of the exhausted IoT devices. Fogging is believed to reduce latency, and enhance efficiency, ease of deployment and flexibility, however, various security and privacy concerns hinder its deployment by major platforms. Among all the security concerns, lack of a proper trust management system is of primary importance. This paper explores the Service-oriented Internet of Things (SIoT) domain to study its similarity with Fogging and creates a trust management scheme (TMS). The paper further explores the necessary trust requirements for Fogging and incorporates them into a two-way trust management scheme based on Bayes model, the model allows both the service requestor and the service provider to validate each other before connecting. The model calculates the value of trust using these metrics and combines them in a unique way with Bayes trust to have an accurate trust value. The proposed scheme is simulated in Netlogo, an agent-based network simulator. The subject scheme is capable of effectively preventing a legitimate node from connecting with a malicious node. The results illustrates high accuracy and faster convergence and also shows resilience against trust-based network attacks. The system is compared against SIoT trust management models due to lack of similar trust management models in Fog Computing.