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The defalsif-AI project: protecting critical infrastructures against disinformation and fake news

In this paper, we describe the concept and ongoing work of the project defalsif-AI, which addresses the protection of critical infrastructures against disinformation and fake news. Defalsif-AI deals particularly with the protection of the main democratic processes and the public trust in democracy a...

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Autores principales: Schreiber, David, Picus, Cristina, Fischinger, David, Boyer, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8447119/
https://www.ncbi.nlm.nih.gov/pubmed/35693024
http://dx.doi.org/10.1007/s00502-021-00929-7
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author Schreiber, David
Picus, Cristina
Fischinger, David
Boyer, Martin
author_facet Schreiber, David
Picus, Cristina
Fischinger, David
Boyer, Martin
author_sort Schreiber, David
collection PubMed
description In this paper, we describe the concept and ongoing work of the project defalsif-AI, which addresses the protection of critical infrastructures against disinformation and fake news. Defalsif-AI deals particularly with the protection of the main democratic processes and the public trust in democracy and its institutions against engineered social media attacks, which, for example, attempt to manipulate the electoral process. Federal ministries and media institutions require new methods and tools to evaluate the ever increasing amount of digital media in terms of identification, verification, and correction of sources. Based on these requirements, the project focuses on research on audio-visual media forensics, text analysis, and multimodal fusion with the support of artificial intelligence (AI) and machine learning methods. One main focus of this research is to make the results more comprehensible and interpretable for non-experts in the forensic/technical field. The primary project outcome is a proof of concept of a multimodal detection platform, which can operate with a variety of sources, including the surface web and social media. Additional research carried out within the project focuses on providing and generating multimodal data necessary to train and test machine learning models. Finally, an analysis and assessment concerning the law and social science are carried out as well.
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spelling pubmed-84471192021-09-17 The defalsif-AI project: protecting critical infrastructures against disinformation and fake news Schreiber, David Picus, Cristina Fischinger, David Boyer, Martin Elektrotech Informationstechnik Originalarbeit In this paper, we describe the concept and ongoing work of the project defalsif-AI, which addresses the protection of critical infrastructures against disinformation and fake news. Defalsif-AI deals particularly with the protection of the main democratic processes and the public trust in democracy and its institutions against engineered social media attacks, which, for example, attempt to manipulate the electoral process. Federal ministries and media institutions require new methods and tools to evaluate the ever increasing amount of digital media in terms of identification, verification, and correction of sources. Based on these requirements, the project focuses on research on audio-visual media forensics, text analysis, and multimodal fusion with the support of artificial intelligence (AI) and machine learning methods. One main focus of this research is to make the results more comprehensible and interpretable for non-experts in the forensic/technical field. The primary project outcome is a proof of concept of a multimodal detection platform, which can operate with a variety of sources, including the surface web and social media. Additional research carried out within the project focuses on providing and generating multimodal data necessary to train and test machine learning models. Finally, an analysis and assessment concerning the law and social science are carried out as well. Springer Vienna 2021-09-17 2021 /pmc/articles/PMC8447119/ /pubmed/35693024 http://dx.doi.org/10.1007/s00502-021-00929-7 Text en © Springer-Verlag GmbH Austria, ein Teil von Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Originalarbeit
Schreiber, David
Picus, Cristina
Fischinger, David
Boyer, Martin
The defalsif-AI project: protecting critical infrastructures against disinformation and fake news
title The defalsif-AI project: protecting critical infrastructures against disinformation and fake news
title_full The defalsif-AI project: protecting critical infrastructures against disinformation and fake news
title_fullStr The defalsif-AI project: protecting critical infrastructures against disinformation and fake news
title_full_unstemmed The defalsif-AI project: protecting critical infrastructures against disinformation and fake news
title_short The defalsif-AI project: protecting critical infrastructures against disinformation and fake news
title_sort defalsif-ai project: protecting critical infrastructures against disinformation and fake news
topic Originalarbeit
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8447119/
https://www.ncbi.nlm.nih.gov/pubmed/35693024
http://dx.doi.org/10.1007/s00502-021-00929-7
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