A Reliable and Decentralized Trust Management Model for Fog Computing in Industrial IoT

Fog computing facilitates low-latency computing and nearby storage of device data in the Industrial Internet of Things (IIoT). Frequent internal interactions between fog nodes can support complex industrial processes, creating a secure fog interaction environment imperative. However, decentralized, mobile, and heterogeneous fog nodes make static cryptography-based security schemes challenging to cope with internal attacks. Adding a trust management model (TMM) to the fog layer is an effective solution to address this issue. Existing fog-oriented TMMs mostly ignore the inconsistent behavior of nodes or blindly trust fake recommendations from highly trusted nodes, which makes TMMs vulnerable to trust attacks from individuals or groups. Also, diverse industrial scenarios require TMMs to sensitively capture changes in fog node behaviors and contexts, rather than relying solely on binary ratings. This paper proposes a reliable distributed trust management model, TFog, to secure industrial IoT fog node interactions. It provides all well-defined model components and their collaboration methods to operate independently on fog nodes in a scalable form. Novel recommendation filtering algorithms, bi-directional interaction rating, and multi-party trust update strategies are proposed to resist trust attacks. Experiments show that TFog has good sensitivity and convergence, also can effectively resist eight typical trust attacks.