In conjunction with 40th AINA-2026 Conference

Victoria University of Wellington, New Zealand 

April 8 to April 10, 2026

Submission deadline: November 15, 2025 

About The Workshop

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As artificial intelligence continues to evolve, its impact on the media landscape has become both transformative and concerning. The ability to manipulate and generate synthetic content at scale has given rise to an era of widespread information disorder, where the authenticity of text, images, and videos is frequently called into question. From deepfakes to AI-generated misinformation, media manipulation presents a pressing global challenge that undermines trust in communication and fuels disinformation campaigns. This workshop focuses on the technological solutions needed to combat these threats and safeguard the integrity of information in the digital age.

STAMM-2026 aims to bring together experts from academia, industry, and research to discuss the latest advancements in AI technology addressing the detection, prevention, and mitigation of media manipulation. The workshop will explore how AI can act both as a catalyst for information disorder and as a solution to its most critical challenges. The event will provide a forum for the exchange of ideas, fostering the development of novel technologies that can restore trust in digital content and protect against AI-driven misinformation.

We invite research contributions that lie at the intersection of AI, media manipulation, and information disorder. Our focus is on solutions that leverage AI to detect manipulated content, defend against adversarial AI techniques, and ensure the authenticity of media within an increasingly fragmented information ecosystem.

Topics

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• AI-driven media manipulation detection and prevention systems
• Deepfakes: creation, detection, and mitigation technologies
• Multimodal AI approaches for detecting manipulated text, images, and video
• Real-Time Detection of Generative AI-Manipulated Media
• Adversarial AI: attack vectors, security challenges, and defense mechanisms
• AI-based content verification, validation, fact-checking, and authentication tools
• Quantum computing solutions for enhancing media integrity
• Generative Adversarial Networks (GANs) for Media Creation and Security
• Blockchain technology for securing digital media authenticity
• Federated learning for decentralized detection of manipulated content
• Machine learning models for detecting AI-generated misinformation
• Advanced natural language processing (NLP) techniques for detecting fake news and misinformation
• AI-based image and video forensics for media authenticity verification
• Computer vision methods for identifying synthetic and manipulated visuals
• Edge computing solutions for distributed AI-based content validation and media integrity
• Neural networks for cross-modal detection of manipulated media
• Explainable AI methods for transparency in media verification processes
• Sentiment analysis for detecting fake news and deceptive content

Submission Information

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Authors should submit original research, ensuring that they are formatted in accordance with the AINA-2026 guidelines. Please visit the following website: AINA-2026 Paper Submission and Publication

All accepted papers will be included in the conference proceedings of Lecture Notes in Data Engineering and Communication Technologies series published by Springer.

Indexing: The books of LNDECT series are indexed by EI and SCOPUS.

Authors of accepted papers, or at least one of them, are requested to register and present their work at the conference (AINA-2026 Registration), otherwise their papers will be removed from the digital library after the conference. 

Please do follow the announcement on the AINA 2026 website.

Workshop Co-Chairs
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Chiara Pero, University of Salerno (Italy), cpero@unisa.it 

Carmen Bisogni, University of Salerno (Italy), cbisogni@unisa.it 

Aniello Castiglione, University of Salerno (Italy), acastiglione@unisa.it

Debiao He, Wuhan University (China), hedebiao@whu.edu.cn

Thomas Tan, Edinburgh Napier University (UK), z.tan@napier.ac.uk