Oct 18, 2026J/K move · Enter open · S save
Benjamin Loison, Quentin Bammey, Thibaud Ehret, Rafael Grompone von Gioi+2
Agence Ministérielle pour l'IA de Défense, France · ENS Paris-Saclay, Université Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France · Télécom Paris, Institut Polytechnique de Paris, LTCI, Palaiseau, France+1
Photo Response Non-Uniformity (PRNU) is widely regarded as the most reliable marker for source camera identification. Recent studies, however, report high correlations between images and fingerprints from different modern smartphones, which calls into question the discriminative power of PRNU on these devices. Using 30 recent smartphones under controlled acquisition conditions (e.g., no digital zoom), we investigate whether the fingerprint itself is at fault or the way it is compared. We find that a component shared by all fingerprints of the same model inflates the standard signed peak-to-correlation energy (sPCE). To counter this, we propose
ΔsPCE: the sPCE between a query image and a candidate camera's fingerprint, minus the mean sPCE between that image and the fingerprints of the remaining candidates, in the spirit of T-norm score normalization.
ΔsPCE improves attribution accuracy, suggesting that the device-specific PRNU signal is still present. Although the limited dataset size and the dependence of
ΔsPCE on the candidate camera set currently restrict operational applicability, these results suggest that PRNU-based attribution of modern smartphones remains feasible when fingerprints are compared appropriately.