A Comparative Analysis on Trust Management Techniques in Internet of Things (IoT)

Cyber Physical Systems is a linked interconnected system of computing devices i.e. objects also called as Things, which are embedded with different types of sensors having unique ID. IoT has a variety of applications that we use in our day-to-day life. Because the number of devices connected to the network is continually expanding, IoT poses a security and privacy risk to end users. Traditional security approaches cannot be applied for IoT security. IoT devices and applications are closely related with society; hence trust is the major issue. Trust management (TM) is an important feature since it ensures system reliability and secure information flow over internet. Information gathering, trust computation, and trust updating are all part of the trust management system. Currently, Trust Management System consists of trust calculation using different methods such as statistical, Bayesian distribution, fuzzy based, blockchain and machine learning. An in-depth study has been carried out in the field of trust management system considering centralized, distributed and semi-distributed architecture; but heterogeneity, scalability of the devices has not been addressed. Healthcare IoT is one of the major domains that utilize IoT framework and services. For enhanced and convenient diagnosis of the diseases, the health data needs to be shared between nodes. This paper presents the detailed review of existing trust calculation methods, trust management systems in Healthcare IoT. According to the research gap discovered, a more effective real-time healthcare monitoring system for supporting timely access to decision-critical information is proposed.