Enhanced adaptive trust management system for socially related IoT

Abstract

The social IoT (SIoT) is a network involving heterogeneous entities like humans, and devices referred to as 'things' are connected with social relationship. Every individual thing has its own ID, functional property, limited storage and capacity. Each one expects to establish trusted communication with other reliable entities in the IoT network, which paves the essential of trust management system (TMS). We propose an adaptive trust management design that performs trust assessment considering both QoS and social parameter for deciding the trustiness of a node in the IoT network. The design uses direct assessment and indirect recommendation, which are aggregated using a dynamic weighted method. The decay factor for the past experiences and dynamic updating of the trust profiles enhances the system performances. The work is compared with static, distributed, social and single trust type of system in terms of resiliency and performance. The proposed work shows very efficient trust assessment and maximum performance.