CTRUST : a dynamic trust model for collaborative applications in the Internet of Things

Abstract

Security through trust presents a viable solution for threat management in the Internet of Things (IoT). Currently, a well-defined trust management framework for collaborative applications on the IoT platform does not exist. In order to estimate reliably the trust values of nodes within a system, the trust should be measured by suitable parameters that are based on the nodes’ functional properties in the application context. Existing models do not clearly outline the parametrization of trust. Also, trust decay is inadequately modeled in most current models. In addition, trust recommendations are usually inaccurately weighted with respect to previous trust, thereby increasing the effect of bad recommendations. A new model, CTRUST, is proposed to resolve these shortcomings. In CTRUST, trust is accurately parametrized while recommendations are evaluated through belief functions. The effects of trust decay and maturity on the trust evaluation process were studied. Each trust component is neatly modeled by appropriate mathematical functions. CTRUST was implemented in a collaborative download application and its performance was evaluated based on the utility derived and its trust accuracy, convergence, and resiliency. The results indicate that IoT collaborative applications based on CTRUST gain a significant improvement in performance, in terms of efficiency and security.