Visualizing and Aggregating Behavior for Trust Evaluation

The Internet of Things or more broadly the Internet of Everything is becoming a possibility in the near future. A vast number of entities (i.e., devices, people, processes etc.) will require to connect to the Internet. These communications could be facilitated by new technologies, such as 5G communication, which aim to be faster by providing higher bandwidth guarantees. This higher network capacity will increase exponentially the volume of data that could be extracted from the Internet regarding individual user or entities' behavior and concurrently the number of attacks that could be deployed. Thus, it is becoming increasing challenging to evaluate the trustworthiness of entities on the Internet. The contribution of this paper is a new methodology of aggregating behavior that aids in evaluating individual trust. We introduce a basic methodology for calculating Trust, which is later extended through clustering of malicious events. Based on the proposed methodology, a GUI is implemented that allows the quick and easy visualization of malicious behavior with the corresponding trust calculation. Overall, this work aims to support existing trust models in terms of aggregating behavior and translating it into trustworthiness.