{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:44:25Z","timestamp":1787028265308,"version":"3.56.0"},"reference-count":90,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Future Internet"],"abstract":"<jats:p>The widespread circulation of digital misinformation exposes a critical shortcoming in prevailing detection strategies, namely, the absence of robust mechanisms to confirm the origin and authenticity of online content. This study addresses this by introducing VeriTrust, a conceptual and provenance-centric framework designed to establish content-level trust by integrating Self-Sovereign Identity (SSI), blockchain-based anchoring, and AI-assisted decentralized verification. The proposed system is designed to operate through three key components: (1) issuing Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs) through Hyperledger Aries and Indy; (2) anchoring cryptographic hashes of content metadata to an Ethereum-compatible blockchain using Merkle trees and smart contracts; and (3) enabling a community-led verification model enhanced by federated learning with future extensibility toward zero-knowledge proof techniques. Theoretical projections, derived from established performance benchmarks, suggest the framework offers low latency and high scalability for content anchoring and minimal on-chain transaction fees. It also prioritizes user privacy by ensuring no on-chain exposure of personal data. VeriTrust redefines misinformation mitigation by shifting from reactive content-based classification to proactive provenance-based verification, forming a verifiable link between digital content and its creator. VeriTrust, while currently at the conceptual and theoretical validation stage, holds promise for enhancing transparency, accountability, and resilience against misinformation attacks across journalism, academia, and online platforms.<\/jats:p>","DOI":"10.3390\/fi17100448","type":"journal-article","created":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T13:52:46Z","timestamp":1759240366000},"page":"448","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Self-Sovereign Identities and Content Provenance: VeriTrust\u2014A Blockchain-Based Framework for Fake News Detection"],"prefix":"10.3390","volume":"17","author":[{"given":"Maruf","family":"Farhan","sequence":"first","affiliation":[{"name":"STEM Department, University of Sussex, The International Study Centre (ISC), Brighton BN1 9RH, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1703-8756","authenticated-orcid":false,"given":"Usman","family":"Butt","sequence":"additional","affiliation":[{"name":"College of Engineering and Information Technology, Ajman University, Ajman P.O. Box 346, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3037-7808","authenticated-orcid":false,"given":"Rejwan Bin","family":"Sulaiman","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Northumbria University, London E1 7HT, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3492-8838","authenticated-orcid":false,"given":"Mansour","family":"Alraja","sequence":"additional","affiliation":[{"name":"Newcastle Business School, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/s11227-024-06671-z","article-title":"An improved multi-modal framework for fake news detection using NLP and Bi-LSTM","volume":"81","author":"Alsuwat","year":"2024","journal-title":"J. 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