IoT trust and reputation: a survey and taxonomy

IoT is one of the fastest-growing technologies and it is estimated that more than a billion devices would be utilized across the globe by the end of 2030. To maximize the capability of these connected entities, trust and reputation among IoT entities is essential. Several trust management models have been proposed in the IoT environment; however, these schemes have not fully addressed the IoT devices features, such as devices role, device type and its dynamic behavior in a smart environment. As a result, traditional trust and reputation models are insufficient to tackle these characteristics and uncertainty risks while connecting nodes to the network. Whilst continuous study has been carried out and various articles suggest promising solutions in constrained environments, research on trust and reputation is still at its infancy. In this paper, we carry out a comprehensive literature review on state-of-the-art research on the trust and reputation of IoT devices and systems. Specifically, we first propose a new structure, namely a new taxonomy, to organize the trust and reputation models based on the ways trust is managed. The proposed taxonomy comprises of traditional trust management-based systems and artificial intelligence-based systems, and combine both the classes which encourage the existing schemes to adapt these emerging concepts. This collaboration between the conventional mathematical and the advanced ML models result in design schemes that are more robust and efficient. Then we drill down to compare and analyse the methods and applications of these systems based on community-accepted performance metrics, e.g. scalability, delay, cooperativeness and efficiency. Finally, built upon the findings of the analysis, we identify and discuss open research issues and challenges, and further speculate and point out future research directions.Comment: 20 pages, 5 Figures, 3 tables, Journal of cloud computin

Consortium blockchain management with a peer reputation system for critical information sharing

Blockchain technology based applications are emerging to establish distributed trust amongst organizations who want to share critical information for mutual benefit amongst their peers. There is a growing need for consortium based blockchain schemes that avoid issues such as false reporting and free riding that impact cooperative behavior between multiple domains/entities. Specifically, customizable mechanisms need to be developed to setup and manage consortiums with economic models and cloud-based data storage schemes to suit various application requirements. In this MS Thesis, we address the above issues by proposing a novel consortium blockchain architecture and related protocols that allow critical information sharing using a reputation system that manages co-operation amongst peers using off-chain cloud data storage and on-chain transaction records. We show the effectiveness of our consortium blockchain management approach for two use cases: (i) threat information sharing for cyber defense collaboration system viz., DefenseChain, and (ii) protected data sharing in healthcare information system viz., HonestChain. DefenseChain features a consortium Blockchain architecture to obtain threat data and select suitable peers to help with cyber attack (e.g., DDoS, Advance Persistent Threat, Cryptojacking) detection and mitigation. As part of DefenseChain, we propose a novel economic model for creation and sustenance of the consortium with peers through a reputation estimation scheme that uses 'Quality of Detection' and 'Quality of Mitigation' metrics. Similarly, HonestChain features a consortium Blockchain architecture to allow protected data sharing between multiple domains/entities (e.g., health data service providers, hospitals and research labs) with incentives and in a standards-compliant manner (e.g., HIPAA, common data model) to enable predictive healthcare analytics. Using an OpenCloud testbed with configurations with Hyperledger Composer as well as a simulation setup, our evaluation experiments for DefenseChain and HonestChain show that our reputation system outperforms state-of-the-art solutions and our consortium blockchain approach is highly scalableIncludes bibliographical references (pages 45-52)