[Paper Review] Fake News, Disinformation, and Deepfakes: Leveraging Distributed Ledger Technologies and Blockchain to Combat Digital Deception and Counterfeit Reality

Paula Fraga‐Lamas, Tiago M. Fernández‐Caramés|arXiv (Cornell University)|Apr 10, 2019

Blockchain Technology Applications and Security13 references87 citations

TL;DR

This paper proposes leveraging Distributed Ledger Technologies (DLTs), particularly blockchain, to combat fake news, disinformation, and deepfakes by ensuring data provenance, traceability, and immutability through decentralized, transparent, and verifiable transaction records. The key contribution is a comprehensive framework for using DLTs to enhance media authenticity and auditability, while identifying critical challenges like scalability, GDPR compliance, and integration with AI for detection.

ABSTRACT

The rise of ubiquitous deepfakes, misinformation, disinformation, propaganda and post-truth, often referred to as fake news, raises concerns over the role of Internet and social media in modern democratic societies. Due to its rapid and widespread diffusion, digital deception has not only an individual or societal cost (e.g., to hamper the integrity of elections), but it can lead to significant economic losses (e.g., to affect stock market performance) or to risks to national security. Blockchain and other Distributed Ledger Technologies (DLTs) guarantee the provenance, authenticity and traceability of data by providing a transparent, immutable and verifiable record of transactions while creating a peer-to-peer secure platform for storing and exchanging information. This overview aims to explore the potential of DLTs and blockchain to combat digital deception, reviewing initiatives that are currently under development and identifying their main current challenges. Moreover, some recommendations are enumerated to guide future researchers on issues that will have to be tackled to face fake news, disinformation and deepfakes, as an integral part of strengthening the resilience against cyber-threats on today's online media.

Motivation & Objective

• Address the growing threat of digital deception, including fake news and deepfakes, which undermine trust in democratic institutions and media.
• Explain how DLTs can provide immutable, transparent, and decentralized records to verify the origin and integrity of digital content.
• Identify key technical and regulatory challenges in deploying DLTs for media authenticity and cybersecurity.
• Guide future research by outlining open issues such as GDPR compliance, quantum vulnerability, and the need for hybrid AI-DLT systems.
• Propose a holistic framework for integrating DLTs into media ecosystems to enhance accountability and reduce the spread of counterfeit reality.

Proposed method

• Utilize blockchain and DLTs to create tamper-proof, time-stamped logs of digital content creation and sharing, ensuring data provenance.
• Implement cryptographic hashing (including perceptual hashing) to detect content similarity and detect manipulated media.
• Integrate contextual metadata (e.g., temporal patterns, geolocation, social context) to validate media authenticity beyond hash comparison.
• Design DLT architectures with optimized consensus mechanisms and decentralization levels tailored to media traceability workloads.
• Propose hybrid systems combining DLTs with AI/NLP to analyze semantic content and detect manipulation at scale.
• Ensure privacy and security by cryptographically securing content and transaction logs, while enabling auditability and access control.

Experimental results

Research questions

• RQ1 How can DLTs be effectively leveraged to ensure the provenance and traceability of digital media in the face of widespread disinformation?
• RQ2 What are the key technical and regulatory challenges in deploying DLT-based systems for combating fake news and deepfakes?
• RQ3 How can DLTs be integrated with AI and NLP to improve the detection and verification of manipulated content?
• RQ4 What are the implications of DLTs for GDPR compliance, especially regarding data subject rights and data anonymization?
• RQ5 In what ways can DLT-based systems balance content moderation, freedom of expression, and privacy protection in social media ecosystems?

Key findings

• DLTs provide a robust foundation for ensuring data provenance and immutability, enabling transparent and verifiable audit trails for digital content.
• Perceptual hashing and semantic similarity indices can help detect manipulated content even when cryptographic hashes differ due to minor alterations.
• Current DLTs face scalability and performance limitations, especially under high-volume media workloads, due to consensus algorithm constraints.
• GDPR compliance remains a significant challenge, particularly regarding data controller responsibilities and the right to be forgotten in immutable ledgers.
• Post-quantum cryptography is essential for future DLT systems, as current cryptographic primitives are vulnerable to quantum attacks.
• A standalone DLT system cannot verify content authenticity; it must be combined with contextual metadata and AI-driven analysis to ensure resilience against data falsification attacks.