research-article

Open access

AMP: authentication of media via provenance

MMSys '21: Proceedings of the 12th ACM Multimedia Systems Conference

Pages 108 - 121

https://doi.org/10.1145/3458305.3459599

Published: 15 July 2021 Publication History

Abstract

Advances in graphics and machine learning have led to the general availability of easy-to-use tools for modifying and synthesizing media. The proliferation of these tools threatens to cast doubt on the veracity of all media. One approach to thwarting the flow of fake media is to detect modified or synthesized media through machine learning methods. While detection may help in the short term, we believe that it is destined to fail as the quality of fake media generation continues to improve. Soon, neither humans nor algorithms will be able to reliably distinguish fake versus real content. Thus, pipelines for assuring the source and integrity of media will be required---and increasingly relied upon. We present AMP, a system that ensures the authentication of media via certifying provenance. AMP creates one or more publisher-signed manifests for a media instance uploaded by a content provider. These manifests are stored in a database allowing fast lookup from applications such as browsers. For reference, the manifests are also registered and signed by a permissioned ledger, implemented using the Confidential Consortium Framework (CCF). CCF employs both software and hardware techniques to ensure the integrity and transparency of all registered manifests. AMP, through its use of CCF, enables a consortium of media providers to govern the service while making all its operations auditable. The authenticity of the media can be communicated to the user via visual elements in the browser, indicating that an AMP manifest has been successfully located and verified.

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Cited By

Pan BStakhanova NRay S(2023)Data Provenance in Security and PrivacyACM Computing Surveys10.1145/359329455:14s(1-35)Online publication date: 22-Apr-2023
https://dl.acm.org/doi/10.1145/3593294
Fotos NDelgado J(2023)Ensuring privacy in provenance information for images2023 24th International Conference on Digital Signal Processing (DSP)10.1109/DSP58604.2023.10167902(1-5)Online publication date: 11-Jun-2023
https://doi.org/10.1109/DSP58604.2023.10167902
Gil RVirgili-Gomà JLópez-Gil JGarcía R(2023)Deepfakes: evolution and trendsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-08605-y27:16(11295-11318)Online publication date: 15-Jun-2023
https://dl.acm.org/doi/10.1007/s00500-023-08605-y
Show More Cited By

Index Terms

AMP: authentication of media via provenance
1. Security and privacy
  1. Security services
    1. Authentication

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Published In

cover image ACM Conferences

MMSys '21: Proceedings of the 12th ACM Multimedia Systems Conference

June 2021

254 pages

ISBN:9781450384346

DOI:10.1145/3458305

General Chairs:
Özgü Alay
University of Oslo and Simula Metropolitan
,
Cheng-Hsin Hsu
National Tsing Hua University
,
Ali C. Begen
Ozyegin University and Networked Media

Copyright © 2021 ACM.

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 July 2021

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MMSys '21

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SIGMM

MMSys '21: 12th ACM Multimedia Systems Conference

September 28 - October 1, 2021

Istanbul, Turkey

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MMSys '21 Paper Acceptance Rate 18 of 55 submissions, 33%;

Overall Acceptance Rate 176 of 530 submissions, 33%

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Cited By

Pan BStakhanova NRay S(2023)Data Provenance in Security and PrivacyACM Computing Surveys10.1145/359329455:14s(1-35)Online publication date: 22-Apr-2023
https://dl.acm.org/doi/10.1145/3593294
Fotos NDelgado J(2023)Ensuring privacy in provenance information for images2023 24th International Conference on Digital Signal Processing (DSP)10.1109/DSP58604.2023.10167902(1-5)Online publication date: 11-Jun-2023
https://doi.org/10.1109/DSP58604.2023.10167902
Gil RVirgili-Gomà JLópez-Gil JGarcía R(2023)Deepfakes: evolution and trendsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-08605-y27:16(11295-11318)Online publication date: 15-Jun-2023
https://dl.acm.org/doi/10.1007/s00500-023-08605-y
Horvitz E(2022)On the Horizon: Interactive and Compositional DeepfakesProceedings of the 2022 International Conference on Multimodal Interaction10.1145/3536221.3558175(653-661)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3536221.3558175
Losavio MPastukov PPolyakova S(2022)Multimedia Objects and Forensic Determinations of Criminal Responsibility2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)10.1109/SETIT54465.2022.9875452(36-44)Online publication date: 28-May-2022
https://doi.org/10.1109/SETIT54465.2022.9875452

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