Internet-of-things and information fusion: Trust perspective survey

Abstract

The advent of Internet-of-Things (IoT) is creating an ecosystem of smart applications and services enabled by a multitude of sensors. The real value of these IoT smart applications comes from analyzing the information provided by these sensors. Information fusion improves information completeness/quality and, hence, enhances estimation about the state of things. Lack of trust and therefore, malicious activities renders the information fusion process and hence, IoT smart applications unreliable. Behavior-related issues associated with the data sources, such as trustworthiness, honesty, and accuracy, must be addressed before fully utilizing these smart applications. In this article, we argue that behavior trust modeling is indispensable to the success of information fusion and, hence, to smart applications. Unfortunately, the area is still in its infancy and needs further research to enhance information fusion. The aim of this article is to raise the awareness and the need of behavior trust modelling and its effect on information fusion. Moreover, this survey describes IoT architectures for modelling trust as well as classification of current IoT trust models. Finally, we discuss future directions towards trustworthy reliable fusion techniques.