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

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Authors: Paula Fraga-Lamas, Tiago M. Fernández-Caramés

Published: 2019-04-10 18:42:45+00:00

AI Summary

This paper explores the potential of Distributed Ledger Technologies (DLTs) and blockchain to combat digital deception, such as deepfakes and misinformation. It reviews current DLT-based initiatives and identifies challenges, offering recommendations for future research to strengthen online media resilience against cyber threats.

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.

Key findings

The paper finds that while DLTs offer promising solutions for enhancing data traceability and authenticity, significant challenges remain. These include optimizing DLT design for specific use cases, ensuring cybersecurity and privacy, and addressing the limitations of current cryptographic techniques in detecting subtle manipulations. Further research is needed to integrate DLTs with AI and NLP for improved detection of digital deception.

Approach

The paper proposes a comprehensive overview of how DLTs can be used to address digital deception. It examines various applications, including decentralized content moderation, trustworthiness checkers, and reputation systems, highlighting their potential benefits and limitations. The authors suggest a multidisciplinary approach combining DLTs with AI and NLP techniques for more effective detection and prevention.

Datasets

UNKNOWN

Model(s)

UNKNOWN

Author countries

Spain

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