Data Privacy Preserving for Multimedia Systems
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 February 2026 | Viewed by 6
Special Issue Editors
Interests: computer vision; multi-modal learning
Interests: computer vision; object tracking; person re-identification; unsupervised learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue focuses on advancing research in privacy-preserving multimodal video analysis and its applications in multimedia systems. With the rapid growth of intelligent video systems leveraging multimodal data (visual, audio, textual, and sensor signals), significant privacy concerns arise due to the sensitive nature of such data. This issue invites original research on innovative algorithms, architectures, and frameworks addressing secure data handling, efficient computation, robust learning, and fair inference across diverse modalities. We encourage submissions on topics such as federated learning, differential privacy, secure cross-modal retrieval, and privacy-aware video generation, alongside real-world deployments and new benchmarks. This Special Issue aims to foster interdisciplinary solutions combining machine learning, computer vision, signal processing, and hardware design to enable secure, scalable, and ethical multimedia systems. We warmly welcome researchers and practitioners to contribute their cutting-edge work to shape the future of privacy-preserving multimedia technologies.
Dr. Min Cao
Prof. Dr. Mang Ye
Guest Editors
Manuscript Submission Information
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Keywords
- privacy-preserving video analysis
- multimodal learning
- federated learning
- cross-modal retrieval
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