Can We Trust Blockchain-IoT Data?
Rashmi E. Ratnayake, Madhusanka Liyanage, Liam Murphy · IEEE Internet of Things Magazine · 2025
The adoption of blockchain technology has expanded significantly across diverse application domains, with the Internet of Things (IoT) emerging as one of its most promising and impactful areas of integration. In these applications, ensuring the trustworthiness of data stored on the blockchain is vital for secure and reliable decision-making. While blockchain offers advantages such as decentralization, immutability, and transparency, these alone are insufficient to guarantee data trustworthiness. Most existing approaches to trust evaluation narrowly focus on data and data source-related aspects, considering limited factors and overlooking how blockchain processes and external systems may influence the data throughout its lifecycle. Relying solely on data and source trust can lead to false confidence, as trust can still be compromised by smart contract flaws, unreliable oracles, or weaknesses in blockchain consensus—factors beyond the scope of data or source evaluation. To address this gap, this article analyses the trustworthiness of blockchain data, with a particular emphasis on IoT use cases, and introduces a categorization of trust-related factors into four key dimensions: data-related, source-related, blockchain-related, and external (third-party or cross-chain) aspects. We highlight the relative significance of the trust factors across various application categories and blockchain architectures, and demonstrate the feasibility of our approach using machine learning on a synthetic dataset, further showing that use-case-specific weighting schemes enable clearer separation between trustworthy and untrustworthy data compared to uniform aggregation. This work provides a structured foundation for building trustworthy IoT–blockchain systems and emphasizes the need for adaptable, context-aware trust assessment models.