Blockchain-based fake news traceability and verification mechanism

Wang, Xiaowan; Xie, Huiyin; Ji, Shan; Liu, Liang; Ding, Hu

doi:10.1016/j.heliyon.2023.e17084

Cited by 6 publications

(2 citation statements)

References 38 publications

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“…The study findings further validate that traceability is positively associated with cost-saving in the context of blockchain technology. Based on the study results, it can be suggested that Blockchain technology can aids in tracing real time energy transactions [ 65 ]. In a blockchain-based Smart grid, transactions can be recorded on a transparent ledger accessible to regulators and other energy firms.…”

Section: Discussionmentioning

confidence: 99%

Blockchain-powered grids: Paving the way for a sustainable and efficient future

Ullah,

Al-Rahmi,

Alblehai

et al. 2024

Heliyon

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Section: Discussionmentioning

confidence: 99%

Blockchain-powered grids: Paving the way for a sustainable and efficient future

Ullah,

Al-Rahmi,

Alblehai

et al. 2024

Heliyon

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“…In recent years, blockchain technology, with its scalability and authority-free nature [5], is being harnessed to combat the spread of fake news [6]. Existing blockchain-based approaches have primarily focused on tracking the provenance and modification history of news articles and associated images [7][8][9][10] or on assigning veracity labels to them [11][12][13]. Blockchain-based veracity labeling approaches typically incorporate voting mechanisms and/or machine learning models to assess the credibility of news.…”

Section: Introductionmentioning

confidence: 99%

Connecting the Dots Between Stance and Fake News Detection with Blockchain, Proof of Reputation, and the Hoeffding Bound

salah,

Jouini,

Pachon

et al. 2024

Preprint

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Combating fake news is a crucial endeavor, yet the complexity of the task requires multifaceted approaches that transcend singular technological solutions. Traditional fact-checking, often centralized and human-dependent, faces scalability and bias challenges. This paper introduces a novel blockchain-based framework that leverages the wisdom of the crowd for an authority-free, scalable, automated and reputation-driven fact-checking. Within this framework, stance detection acts as an automated means of opinion retrieval, while the Proof of Reputation consensus mechanism fosters an environment where reputable contributors have greater influence in shaping news credibility. Concurrently, the Hoeffding bound is used to allow the system to adapt to evolving contexts. In contrast to Machine Learning -based approaches, our framework avoids the need for periodic retraining to update a model’s frozen knowledge of the world. The experimental study conducted on real-world data demonstrates that the proposed framework offers a promising and efficient solution to combat the spread of fake news.

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