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InfoResearchPeer-reviewed
Source Camera Model Identification via Federated Learning Using Laplacian-Based Patches
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Summary
Researchers present FedFFTNet, a lightweight dual-branch deep learning architecture that identifies source camera models from pattern noise using federated learning, so training data stays private. A Laplacian-based patch selection strategy focuses on sharp image regions to improve feature extraction. On four benchmark datasets (Forchheim, Dresden, Vision, Socrates) under the federated setup, the system reports image-level accuracy of 99.10%, 99.78%, 98.64% and 97.38%.