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In the era of Generative AI, the creation and manipulation of digital content have reached unprecedented levels of scale, realism, and automation. Technologies powered by Large Language Models (LLMs) and deepfake generators now enable the production of highly convincing synthetic media—including text, audio, video, and images—that blur the line between fact and fabrication. These tools are increasingly exploited to spread disinformation, distort public discourse, and amplify digital polarization across online platforms. As synthetic content proliferates across social media, news sites, and forums, existing moderation and trust mechanisms are struggling to keep pace. This raises critical challenges for content authentication, platform governance, and the robustness of our online information ecosystem.
This Special Issue seeks to bring together researchers, system designers, and practitioners who are developing technologies and methodologies to understand, detect, and mitigate the misuse of generative AI in Internet-based systems. We welcome contributions that are practical, applied, and system-oriented, including prototypes, deployment studies, and empirical evaluations.
We invite original research articles, system designs, critical analyses, and interdisciplinary studies including—but not limited to—the following areas:
For author information and guidelines on submission criteria, visit the Author’s Information Page. Please submit papers through the IEEE Author Portal and be sure to select the special issue or special section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts. If requested, abstracts should be sent by email to the guest editors directly.
In addition to submitting your paper to IEEE Internet Computing, you are also encouraged to upload the data related to your paper to IEEE DataPort. IEEE DataPort is IEEE’s data platform that supports the storage and publishing of datasets while also providing access to thousands of research datasets. Uploading your dataset to IEEE DataPort will strengthen your paper and will support research reproducibility. Your paper and the dataset can be linked, providing a good opportunity for you to increase the number of citations you receive. Data can be uploaded to IEEE DataPort prior to submitting your paper or concurrent with the paper submission. Thank you!
Contact the guest editors at: pallis@ucy.ac.cy
Guest Editors:
