Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Gagnon, S.
"Use of AI to Fight Disinformation and Corruption" Article d'actes
Dans: Am. Conf. Inf. Syst., AMCIS, p. 4853–4854, Association for Information Systems, 2025, ISBN: 979-833132774-3 (ISBN).
Résumé | Liens | BibTeX | Étiquettes: Action research, Audio videos, Copyrights, Crime, Due diligence, Information leakage, Information use, Institutional change, Integrated strategy, Knowledge graph, Knowledge graphs, Open source intelligence, Open systems, Research advances
@inproceedings{gagnon_use_2025,
title = {"Use of AI to Fight Disinformation and Corruption"},
author = {S. Gagnon},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105025353954&partnerID=40&md5=fc3ca73e0de02b06fd218e03588f3e22},
isbn = {979-833132774-3 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Am. Conf. Inf. Syst., AMCIS},
volume = {7},
pages = {4853–4854},
publisher = {Association for Information Systems},
abstract = {Disinformation (false information disseminated with the intent to cause harm) takes many forms, including fake news, audio-video impersonations, data falsification, and more. It is linked to allegations of corruption and fraud against elected officials, which, once disambiguated (whether true or false), will in all cases require immediate action to preserve democracy. An integrated strategy to combat disinformation and corruption is needed, requiring constant vigilance, due diligence, and open-source intelligence (OSINT) collaboration. Our PDS will explore how AI, especially LLMs and Knowledge Graphs, can serve this purpose and automate the necessary means to combat hybrid threats to democracy. The PDS will cover the following issues and latest research advances, allowing also interactive roundtables to ensure participants can contribute insight to the debate: 1. Presentation: fighting jointly against disinformation and corruption 2. Roundtable: what innovations are most effective in combating hybrid threats? 3. Demo: ai and knowledge graphs to disambiguate allegations against elected officials 4. Roundtable: what institutional changes are required to fight hybrid threats? 5. Conclusion: action research helping parliamentary institutions develop AI capabilities. Copyright © 2025 by Association for Information Systems (AIS). All rights reserved.},
keywords = {Action research, Audio videos, Copyrights, Crime, Due diligence, Information leakage, Information use, Institutional change, Integrated strategy, Knowledge graph, Knowledge graphs, Open source intelligence, Open systems, Research advances},
pubstate = {published},
tppubtype = {inproceedings}
}
Disinformation (false information disseminated with the intent to cause harm) takes many forms, including fake news, audio-video impersonations, data falsification, and more. It is linked to allegations of corruption and fraud against elected officials, which, once disambiguated (whether true or false), will in all cases require immediate action to preserve democracy. An integrated strategy to combat disinformation and corruption is needed, requiring constant vigilance, due diligence, and open-source intelligence (OSINT) collaboration. Our PDS will explore how AI, especially LLMs and Knowledge Graphs, can serve this purpose and automate the necessary means to combat hybrid threats to democracy. The PDS will cover the following issues and latest research advances, allowing also interactive roundtables to ensure participants can contribute insight to the debate: 1. Presentation: fighting jointly against disinformation and corruption 2. Roundtable: what innovations are most effective in combating hybrid threats? 3. Demo: ai and knowledge graphs to disambiguate allegations against elected officials 4. Roundtable: what institutional changes are required to fight hybrid threats? 5. Conclusion: action research helping parliamentary institutions develop AI capabilities. Copyright © 2025 by Association for Information Systems (AIS). All rights reserved.
2.
Allili, M. S.; Casemajor, N.; Talbi, A.
Multiple image copy detection and evolution visualisation using tree graphs Article de journal
Dans: Multimedia Tools and Applications, vol. 78, no 5, p. 6253–6275, 2019, ISSN: 13807501, (Publisher: Springer New York LLC).
Résumé | Liens | BibTeX | Étiquettes: Copy detection, Copyright protections, Copyrights, Forestry, Image copy detection, Image Enhancement, Image indexing, Image transformations, Multiple image, Original images, Tree graph, Trees (mathematics)
@article{allili_multiple_2019,
title = {Multiple image copy detection and evolution visualisation using tree graphs},
author = {M. S. Allili and N. Casemajor and A. Talbi},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050295791&doi=10.1007%2fs11042-018-6350-5&partnerID=40&md5=21d91677491c36f971e27b7168f5b3dc},
doi = {10.1007/s11042-018-6350-5},
issn = {13807501},
year = {2019},
date = {2019-01-01},
journal = {Multimedia Tools and Applications},
volume = {78},
number = {5},
pages = {6253–6275},
publisher = {Springer New York LLC},
abstract = {Image copy detection is an important problem for several applications such as detecting forgery to enforce copyright protection and intellectual property. One of the important problems following copy detection, however, is the assessment of the type of modifications undergone by an original image to form its copies. In this work, we propose a method for quantifying some of these modifications when multiple copies of the same image are available. We also propose an algorithm to estimate temporal precedence between images (i.e., the order of creation of the copies). Using the estimated relations, a tree graph is then built to visualize the history of evolution of the original image into its copies. Our work is important for ensuring better interpretation of image copies after their detection. It also lays a new ground for enhancing image indexing, dissemination analysis and search on the Web. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.},
note = {Publisher: Springer New York LLC},
keywords = {Copy detection, Copyright protections, Copyrights, Forestry, Image copy detection, Image Enhancement, Image indexing, Image transformations, Multiple image, Original images, Tree graph, Trees (mathematics)},
pubstate = {published},
tppubtype = {article}
}
Image copy detection is an important problem for several applications such as detecting forgery to enforce copyright protection and intellectual property. One of the important problems following copy detection, however, is the assessment of the type of modifications undergone by an original image to form its copies. In this work, we propose a method for quantifying some of these modifications when multiple copies of the same image are available. We also propose an algorithm to estimate temporal precedence between images (i.e., the order of creation of the copies). Using the estimated relations, a tree graph is then built to visualize the history of evolution of the original image into its copies. Our work is important for ensuring better interpretation of image copies after their detection. It also lays a new ground for enhancing image indexing, dissemination analysis and search on the Web. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.