Deep steganographic approach for reliable data hiding using convolutional neural networks and adaptive loss optimization
Malathi P., Gireesh Kumar T. · 2025
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Description
Malathi and Gireesh Kumar propose a deep learning system for hiding data inside images in 2025. Their design chains three convolutional networks: one prepares the secret, one embeds it in a cover image, and one reveals it again.
Among four candidate loss functions, the third, which balances mean and variance terms, worked best. It carried three to five bits per pixel while keeping image quality high across several datasets. The hidden data survived Gaussian noise, cropping and rotation, and steganalysis tools rarely detected it. Compared with generative adversarial approaches, the method offered a better balance of capacity and robustness at lower computing cost, with medical imaging named as one use.
Catalog record
| CREATOR | Malathi P., Gireesh Kumar T. |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 97 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |