Combating Deepfakes: Multi-LSTM and Blockchain as Proof of Authenticity for Digital Media

Christopher Chun Ki Chan, Vimal Kumar, Steven Delaney, Munkhjargal Gochoo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

Malicious use of deep learning algorithms has allowed the proliferation of high realism fake digital content such as text, images, and videos, to exist on the internet as readily available and accessible consumable content. False information provided through algorithmically modified footage, images, audios, and videos (known as deepfakes), coupled with the virality of social networks, may cause major social unrest. The emergence of misinformation from fabricated digital content suggests the necessity for anti-disinformation methods such as deepfake detection algorithms or immutable metadata in order to verify the validity of digital content. Permissioned blockchain, notably Hyperledger Fabric 2.0, coupled with LSTMs for audio/video/descriptive captioning is a step towards providing a feasible tool for combating deepfake media. Original content would require the original artist attestation of untampered data. The smart contract combines a varied multiple LSTM networks into a process that allows for the tracing and tracking of a digital content's historical provenance. The result is a theoretical framework that enables proof of authenticity (PoA) for digital media using a decentralized blockchain using multiple LSTMs as a deep encoder for creating unique discriminative features; which is then compressed and hashed into a transaction. Our work assumes we trust the video at the point of reception. Our contribution is a decentralized blockchain framework of deep discriminative digital media to combat deepfakes.

Original languageEnglish
Title of host publication2020 IEEE / ITU International Conference on Artificial Intelligence for Good, AI4G 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages55-62
Number of pages8
ISBN (Electronic)9781728170312
DOIs
Publication statusPublished - Sept 21 2020
Event2020 IEEE / ITU International Conference on Artificial Intelligence for Good, AI4G 2020 - Geneva, Switzerland
Duration: Sept 21 2020Sept 25 2020

Publication series

Name2020 IEEE / ITU International Conference on Artificial Intelligence for Good, AI4G 2020

Conference

Conference2020 IEEE / ITU International Conference on Artificial Intelligence for Good, AI4G 2020
Country/TerritorySwitzerland
CityGeneva
Period9/21/209/25/20

Keywords

  • artificial intelligence
  • blockchain
  • computer vision
  • deepfake
  • smart contracts

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Combating Deepfakes: Multi-LSTM and Blockchain as Proof of Authenticity for Digital Media'. Together they form a unique fingerprint.

Cite this