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AI-generated contents have taken the world by storm. AI-generated contents now spans a wide range, including AI-generated videos, images, audios, and texts. Fueled by the accessibility of large-scale media datasets and the maturity of AI generation technologies, currently one may effortlessly create massive forgery images, videos, audios, and texts beyond human discernibility. These medias play important roles in filmmaking, electronic games, image editing, and education. It is thus not surprising that generative AI is redefining the video industry and many other industries. However, despite their positive widespread use, malicious actors can leverage advances in AI generation technologies for nefarious purposes. They may forge high-quality artifacts to perform scam, generate and propagate fake pornography, and challenge face recognition systems, to name a few. To alleviate the abuse of AI generation technologies, it is of paramount importance to develop sound detection and tracking approaches.
This special issue aims to bring together the cutting-edge advancements in AI content generation and detection, diving deeper into AI image generation, AI video generation, AI audio generation, AI text generation, and AI generated content detection tasks. We are interested in AI-Generated data covering a wide scope, from images, audios, texts, to videos. We expect the contributions focusing on innovative techniques for AI content generation and detection, including methodologies and algorithmic approaches to solve theoretical and practical problems. We also encourage the research on potentially impactful and related technologies.
The topics of interest for the Special Issue encompass, but are not limited to:
For author information and guidelines on submission criteria, please visit the Author Information Page. Please submit papers through the IEEE Author Portal, and be sure to select the special-issue name. Manuscripts should be written in English and describe original research. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, The review process will comply with the standard review process of the IEEE Transactions on Dependable and Secure Computing journal. All submitted papers will be evaluated on the basis of relevance, significance of contribution, and technical quality.
In addition to submitting your paper to IEEE Transactions on Dependable and Secure 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!
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