Trustworthiness and explainability of a watermarking and machine learning-based system for image modification detection to combat disinformation-Reference-Cited by-同舟云学术

Trustworthiness and explainability of a watermarking and machine learning-based system for image modification detection to combat disinformation

Published:2024-07-30 Issue: Volume:14 Page:1-10
ISSN:
Container-title:Proceedings of the 19th International Conference on Availability, Reliability and Security
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Author:

Rosales Andrea¹^ORCID,Malanowska Agnieszka²^ORCID,Koohpayeh Araghi Tanya³^ORCID,Kuribayashi Minoru⁴^ORCID,Kowalczyk Marcin²^ORCID,Blanche-Tarragó Daniel¹^ORCID,Mazurczyk Wojciech²^ORCID,Megías David³^ORCID

Affiliation:

1. Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya, Spain

2. Warsaw University of Technology, Poland

3. Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya, Barcelona, Spain, Spain and Center for Cybersecurity Research of Catalonia (CYBERCAT), Spain

4. Center for Data-driven Science and Artificial Intelligence at Tohoku University Japan, Japan

Funder

Japan Science and Technology Agency award number(s): Detection of fake newS on SocIal MedIa pLAtfoRms project from the EIG CONCERT-Japan

Ministerio de Ciencia e Innovación, the Agencia Estatal de Investigación, and the European Regional Development Fund (ERDF) award number(s): SECURING

Government of Spain award number(s): Detection of fake newS on SocIal MedIa pLAtfoRms project from the EIG CONCERT-Japan

National Centre for Research and Development, Poland award number(s): Detection of fake newS on SocIal MedIa pLAtfoRms project from the EIG CONCERT-Japan

DANGER Strategic Project of Cybersecurity- Next Generation EU and the Recovery, Transformation and Resilience Plan

ARTEMISA International Chair of Cybersecurity - Next Generation EU and the Recovery, Transformation and Resilience Plan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3664476.3670934

Reference29 articles.

1. Tanya Koohpayeh Araghi, Ala Abdulsalam Alarood, and Sagheb Kohpayeh Araghi. 2021. Analysis and Evaluation of Template Based Methods Against Geometric Attacks: A Survey. In Innovative Systems for Intelligent Health Informatics, Faisal Saeed, Fathey Mohammed, and Abdulaziz Al-Nahari (Eds.). Springer International Publishing, Cham, 807–814.

2. Analysis and effectiveness of deeper levels of SVD on performance of hybrid DWT and SVD watermarking

3. Disinformation detection and source tracking using semi-fragile watermarking and blockchain

4. Emma Bowman. 2023. Security forces regain control after Bolsonaro supporters storm Brazil’s Congress. https://www.npr.org/2023/01/08/1147757260/bolsonaro-supporters-storm-brazil-congress-lula

5. Xception: Deep Learning with Depthwise Separable Convolutions