Metraipolis › archive › dc_7c4a6da040ff

Can Tainted Pixels Expose Deepfake Videos? — arXiv:2608.27492

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.27492
License (as archived): CC0-1.0
Archived: 2026-10-17T10:58:10.105Z
SHA-256 of the archived text: 51906d2f27c865ee07d94efbe4ebcbd9cc9910c069286111c4e0fad9427223f8
Stable URL of this page: https://metraipolis.com/documento/dc_7c4a6da040ff

How to cite

Can Tainted Pixels Expose Deepfake Videos? — arXiv:2608.27492 — arXiv (en), https://arxiv.org/abs/2608.27492 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_7c4a6da040ff (Metraipolis archive dc_7c4a6da040ff, sha256 51906d2f27c865ee07d94efbe4ebcbd9cc9910c069286111c4e0fad9427223f8)

BibTeX

@misc{dc7c4a6da040ff,
  title = {Can Tainted Pixels Expose Deepfake Videos? — arXiv:2608.27492},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.27492},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_7c4a6da040ff; sha256 51906d2f27c865ee07d94efbe4ebcbd9cc9910c069286111c4e0fad9427223f8},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.27492. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Publicly-acceesible face-manipulation tools have made deepfake creation accessible to non-expert users. Against these, existing defenses are mostly post-hoc, detecting only after forgery has occurred, and operating on still images rather than videos. Research is lacking in i) the proactive protection of published facial videos against black-box manipulation tools, and in (ii) understanding its perceptual effect on human viewers. We introduce TaintedPixels, a proactive video-protection method built around an asymmetric visibility trade-off: the embedded watermark should remain inconspicuous in the published video but become obvious once a downstream tool manipulates the video. TaintedPixels injects structured periodic perturbations into the blue channel of facial regions and refines them under stripe-visibility, color-cast, and video-level LPIPS budgets, with lightweight motion-adaptive deployment. We believe TaintedPixels is the first proactive defense designed specifically against black-box manipulation tools rather than image-level pipelines or specific surrogate generators. Across three publicly available off-the-shelf video manipulation tools and two off-the-shelf detectors, TaintedPixels attains the highest forgery fake rate while keeping perturbations small (LPIPS = 0.0042). Our non-expert human study, conducted on a diverse set of 300 video stimuli spanning different lighting conditions, backgrounds, and skin tones, shows that protected source videos draw a 3.26% suspicion rate, while forgeries from protected sources are identified as fake much more often than forgeries from unprotected sources (90.72% vs. 56.71%). This validates the effectiveness of TaintedPixels.

Tema degli esploratori: fiducia digitale e crittografia (retro-catalogo arXiv: annunci del 2026-08-31 in cs.CR).
Categorie arXiv: Cryptography and Security (cs.CR) ; Computer Vision and Pattern Recognition (cs.CV).
Pagina del lavoro: https://arxiv.org/abs/2608.27492 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-17T10:49:51.618Z dalla pagina https://arxiv.org/catchup/cs.CR/2026-08-31?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).