Apple's Synthetic Defocus Noise Pattern: Characterization and Forensic Applications

iPhone portrait-mode images contain a distinctive pattern in out-of-focus regions simulating the bokeh effect, which we term Apple's Synthetic Defocus Noise Pattern (SDNP). If overlooked, this pattern can interfere with blind forensic analyses, especially PRNU-based camera source verification, as noted in earlier works. Since Apple's SDNP remains underexplored, we provide a detailed characterization, proposing a method for its precise estimation, modeling its dependence on scene brightness, ISO settings, and other factors. Leveraging this characterization, we explore forensic applications of the SDNP, including traceability of portrait-mode images across iPhone models and iOS versions in open-set scenarios, assessing its robustness under post-processing. Furthermore, we show that masking SDNP-affected regions in PRNU-based camera source verification significantly reduces false positives, overcoming a critical limitation in camera attribution, and improving state-of-the-art techniques.

@article{vázquez-padín2025_2505.07380,
  title={ Apple's Synthetic Defocus Noise Pattern: Characterization and Forensic Applications },
  author={ David Vázquez-Padín and Fernando Pérez-González and Pablo Pérez-Miguélez },
  journal={arXiv preprint arXiv:2505.07380},
  year={ 2025 }
}