A Blockchain-Identity Based Cybersecurity Trust Concept for Inter-Device Interactions in IoT Ecosystems

Abstract

The rapid expansion of the Internet of Things creates challenges of trust and security among heterogeneous devices. This paper presents a blockchain-based trust model that integrates reputation from past interactions with blockchain-verified identities and contextual factors. The model was formalized mathematically and implemented through a smart contract prototype. Experiments in simulated IoT networks showed that malicious nodes are detected after 3-5 suspicious interactions, achieving about 91% accuracy with verification delays near 240 ms for 500 devices. The optimal trust threshold was identified at $\tau=0.6$, ensuring a balance between detection accuracy and false positives. This paper proposes a blockchain-identity based adaptive trust framework that integrates reputation, contextual interaction analysis, and decentralized identity verification, transforming trust into a measurable metric for secure and scalable IoT infrastructures.