This Special Issue presents a curated collection of advanced research contributions addressing security, privacy, and trust in the convergence of blockchain technologies and the Internet of Things. As these technologies increasingly underpin data-driven and autonomous systems in domains such as healthcare, industrial infrastructures, and smart homes, ensuring their resilience and trustworthiness has become a critical research and engineering challenge.

The contributions assembled in this Special Issue reflect the maturity of the field by combining foundational analyses with practical, system-oriented solutions. Topics range from structured threat models, vulnerability analyses, and privacy challenges in decentralized environments to intelligent detection mechanisms based on machine learning, explainable artificial intelligence, and federated learning. The Special Issue also provides a comprehensive overview how blockchain based security mechanisms can be integrated into real world, security critical applications, addressing requirements such as data integrity, auditability, accountability, and regulatory compliance.

A pivotal characteristic of this Special Issue is its explicit emphasis on trust as a unifying concept that links security mechanisms, privacy-preserving designs, and data-centric decision-making. By bridging theoretical rigor with experimentally validated systems and applied case studies, this Special Issue offers researchers and practitioners a coherent and timely perspective on the evolving challenges and solutions for secure, privacy preserving, and trustworthy data ecosystems.