ZONIA: a Zero-Trust Oracle System for Blockchain IoT Applications
Lorenzo Gigli, Ivan Zyrianoff, Federico Montori, Luca Sciullo, Carlos Kamienski, Marco Di Felice
TL;DR
ZONIA presents a zero-trust blockchain oracle network tailored for IoT data, addressing centralization and trust issues by decoupling data sources from clients and enabling anonymous participation. The architecture combines semantic and geospatial querying with VRF-based, reputation-driven node selection, a deterministic truth-inference mechanism, and a comprehensive on-chain/off-chain data gathering workflow. Empirical and analytical evaluations demonstrate scalable performance and resilience to data falsification and collusion, with high truth accuracy even when up to 40% of participating entities are malicious, and a practical framework for maintaining data integrity in IoT contexts. The work offers a practical pathway to reliable IoT data exchange in decentralized applications, with implications for smart insurance, environmental monitoring, and other data-sensitive domains, while suggesting future enhancements like predictive analytics and caching to boost performance.
Abstract
The rapid expansion of the Internet of Things (IoT) has led to significant data reliability and system transparency challenges, aggravated by the centralized nature of existing IoT architectures. This centralization often results in siloed data ecosystems, where interoperability issues and opaque data handling practices compromise both the utility and trustworthiness of IoT applications. To address these issues, we introduce ZONIA (Zero-trust Oracle Network for IoT Applications), a novel blockchain oracle system designed to enhance data integrity and decentralization in IoT environments. Unlike traditional approaches that rely on Trusted Execution Environments and centralized data sources, ZONIA utilizes a decentralized, zero-trust model that allows for anonymous participation and integrates multiple data sources to ensure fairness and reliability. This paper outlines ZONIA's architecture, which supports semantic and geospatial queries, details its data reliability mechanisms, and presents a comprehensive evaluation demonstrating its scalability and resilience against data falsification and collusion attacks. Both analytical and experimental results demonstrate ZONIA's scalability, showcasing its feasibility to handle an increasing number of nodes in the system under different system conditions and workloads. Furthermore, the implemented reputation mechanism significantly enhances data accuracy, maintaining high reliability even when 40\% of nodes exhibit malicious behavior.