Threat Modeling a Health Web3 DApp

• Autor(es): Gomes, Ricardo ; Dinis, Daniela ; Oliveira, João ; Maximiano, Marisa ; Távora, Vítor ; Antunes, Carlos Machado ; Dias, Manuel ; Bezerra, Ricardo Correia
• Data: 2025
• Origem: Journal of Digital Media & Interaction
• Tipo de Documento: Artigo científico
• Idioma: Inglês

Descrição

The healthcare sector increasingly explores Distributed Ledger Technology (DLT) and Health Web 3.0 Decentralized Applications (DApps) as promising solutions for patient-centric data management, data sovereignty, and privacy-preserving systems. Despite significant research at the intersection of blockchain and healthcare, current efforts predominantly address isolated technical challenges—focusing narrowly on specific mechanisms such as confidentiality, privacy, or individual smart contract vulnerabilities. Even cybersecurity assessments typically examine discrete attack vectors rather than comprehensive threat landscapes. This fragmented approach limits our ability to build trustworthy systems and delays real-world adoption, as stakeholders lack frameworks to holistically evaluate security posture.This study addresses this gap by conducting a comprehensive threat modeling analysis of Health Web 3.0 DApps, taking into account the complex and interconnected security challenges inherent in blockchain-based healthcare systems. We employ a multi-framework approach integrating LINDDUN threat modeling methodology, OWASP Top 10 Smart Contract Vulnerabilities catalog, and Threat Dragon analytical tool to systematically identify, categorize, and evaluate security risks across the entire application stack. Our analysis maps threats spanning smart contract design flaws, cross-chain interaction vulnerabilities, decentralized identity management weaknesses, unauthorized data access risks, and denial-of-service attack vectors.The primary contribution of this work is demonstrating the critical importance and practical value of holistic threat modeling in blockchain healthcare systems. Our findings reveal interdependencies between seemingly isolated vulnerabilities and show how comprehensive security assessment enhances data privacy protection, smart contract integrity, and overall application resilience. This research provides stakeholders with a systematic methodology for deriving trust in blockchain healthcare solutions, advancing both regulatory compliance and user confidence in decentralized medical data management systems.