An International Standard For Assessing Trustworthiness In Media

The proliferation of synthetic media generation technologies, such as generative AI, has led to a surge of media content generation and consumption. While this progress opens new opportunities, especially in creative industries, it also causes challenges, including piracy, fake media distribution, and concerns about trust and privacy. In the creative sector, media modifications are often part of the production pipelines and in many application domains, creators need or want to declare the type of modifications that were performed on the media asset. The cryptographically signed association of provenance information with the media asset itself provides a trust link between the owner or editor of a media asset and its consumers. The absence of such assertions may reveal the lack of trustworthiness in media assets or worse, the intention to hide the existence of manipulations. This paper describes the JPEG Trust framework (ISO/IEC 21617) that aims to establish trust in digital media creation, modification, annotation, distribution and consumption. The framework provides standardized protocols to extract indicators to assess trustworthiness, means to annotate media provenance, and securely link the assets and associated annotations together.

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Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/icip51287.2024.10647585
Citations
3
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
3.40
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article

An International Standard For Assessing Trustworthiness In Media

Leonard Rosenthol, Zi-Yuan Hu, Frederik Temmermans, Sabrina Caldwell et al.
3 citations
Misinformation and Its Impacts
3.40
article

An International Standard For Assessing Trustworthiness In Media

Leonard Rosenthol, Zi-Yuan Hu, Frederik Temmermans, Sabrina Caldwell, Fernando Pereira, Jaime Delgado, Touradj Ebrahimi, Deepayan Bhowmik, Xiaojun Gu, Nikolaos Fotos, Haibo Zhou, Xin Kang
article en
3 citations

Abstract

The proliferation of synthetic media generation technologies, such as generative AI, has led to a surge of media content generation and consumption. While this progress opens new opportunities, especially in creative industries, it also causes challenges, including piracy, fake media distribution, and concerns about trust and privacy. In the creative sector, media modifications are often part of the production pipelines and in many application domains, creators need or want to declare the type of modifications that were performed on the media asset. The cryptographically signed association of provenance information with the media asset itself provides a trust link between the owner or editor of a media asset and its consumers. The absence of such assertions may reveal the lack of trustworthiness in media assets or worse, the intention to hide the existence of manipulations. This paper describes the JPEG Trust framework (ISO/IEC 21617) that aims to establish trust in digital media creation, modification, annotation, distribution and consumption. The framework provides standardized protocols to extract indicators to assess trustworthiness, means to annotate media provenance, and securely link the assets and associated annotations together.

Australian National University (AU), Adobe Systems (United States) (US), Vrije Universiteit Brussel (BE), Huawei Technologies (China) (CN), Instituto de Telecomunicações (PT), FC Barcelona (ES), École Polytechnique Fédérale de Lausanne (CH), Newcastle University (GB), Universitat Politècnica de Catalunya (ES)
Partnerships for the goals
Openalex Percentile: Top 7%
Misinformation and Its Impacts
3.40
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