Fake News: A Technological Approach to Proving the Origins of Content, Using Blockchains

Abstract

In this article, we introduce a prototype of an innovative technology for proving the origins of captured digital media. In an era of fake news, when someone shows us a video or picture of some event, how can we trust its authenticity? It seems that the public no longer believe that traditional media is a reliable reference of fact, perhaps due, in part, to the onset of many diverse sources of conflicting information, via social media. Indeed, the issue of "fake" reached a crescendo during the 2016 U.S. Presidential Election, when the winner, Donald Trump, claimed that The New York Times was trying to discredit him by pushing disinformation. Current research into overcoming the problem of fake news does not focus on establishing the ownership of media resources used in such stories-the blockchain-based application introduced in this article is technology that is capable of indicating the authenticity of digital media. Put simply, using the trust mechanisms of blockchain technology, the tool can show, beyond doubt, the provenance of any source of digital media, including images used out of context in attempts to mislead. Although the application is an early prototype and its capability to find fake resources is somewhat limited, we outline future improvements that would overcome such limitations. Furthermore, we believe that our application (and its use of blockchain technology and standardized metadata) introduces a novel approach to overcoming falsities in news reporting and the provenance of media resources used therein. However, while our application has the potential to be able to verify the originality of media resources, we believe that technology is only capable of providing a partial solution to fake news. That is because it is incapable of proving the authenticity of a news story as a whole. We believe that takes human skills.

Using Blockchain to Rein in the New Post-Truth World and Check the Spread of Fake News

“…H(nonce prev hash tx 1 tx 2 ... tx n ) < target (1) 5) Blockchain To Check Fake News: In a recent study [6], an Ethereum blockchain enabled prototype framework is proposed for verification of content's credibility. The proposed solution uses preservation metadata implementation strategies (PREMIS) for cryptographically storing digital media on the blockchain.…”

Social media and its intersections with free speech, freedom of information and privacy. An analysis

“…Anyway, technological and automated solutions might provide only a partial solution to this problem, as they would never prove the authenticity of a piece of news as a whole and focus mostly on distribution patterns (Huckle & White, 2017). Encouraging collaborative and social evaluation of the sources and pieces of news distributed could be an additional feature to be implemented.…”

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

“…i) Provenance and ownership: the use of DLT technology would also allow for making content forgery almost impossible by demonstrating its origin and, in case of detecting a counterfeit, it would make the owner accountable. For instance, Huckle et al [16] proposed an Ethereum framework with standardized metadata for the verification of the authenticity and the provenance of digital media. Such a prototype uses Interplanetary File System (IPFS) [17], a P2P contentaddressed file system.…”

“…However, the ability of the proposed system to find fake resources is somewhat limited (i.e., it is not able to prove the authenticity of a story as a whole). A similar solution is described in [16], where the authors present an early prototype of the 'Provenator', which stores provenance metadata (i.e., objects, events, agents and rights) on an Ethereum blockchain that allows users to check the provenance of media resources. The solution assumes that the Provenator was used to document the resource in the first place.…”

“…• The current efforts of the research community are mostly focused on one type of fake news (i.e., verifiable false content), while other bad practices are barely studied. • Most digital deception detection proposals are based on cryptographic hashes, which are sensitive to noise and, when there is a change of a character, a pixel or a bit in a certain content, it can result in a different hash [16]. While any minimal change in two resources will generate vastly different hashes, the use of perceptual hashes produces comparable results if the resources are similar.…”