Privacy-Preserving Model of IoT Based Trust Evaluation

Abstract

With the popularization of Internet of things (IoT), the interaction between human and IoT has become a daily life. In this interaction, the objects of IoT usually require access to personal data, which are often sensitive. We propose a lightweight privacy-preserving model based on the trust evaluation that it can effectively protect privacy based on simple threshold detection. The key issue we address in this work is how to construct trust model so that non trusted objects were prevented from accessing private data. This work can be considered as a lightweight approach to access control for privacy-preservation. The main algorithm in the proposed model is a kind of dynamic self-adjusting trust evaluation mechanism that uses a combination of interaction information occurs between the human and the Internet of things, between the human and the human. According to the given threshold, the trust model can determine the data level of object access in the IoT. We have implemented a prototype of the proposed scheme, thereby demonstrating the feasibility of the proposed scheme on resource-constrained devices.