PRNU Emphasis: a Generalization of the Multiplicative Model

Fernández-Menduiña, Samuel; Pérez-González, Fernando; Masciopinto, Miguel

doi:10.48550/arxiv.2202.12357

Cited by 1 publication

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“…In [ 16 ], Masciopinto and Pérez-González thoroughly investigated the PRNU model and concluded that a revision is needed. In [ 17 ], the same authors proposed a new generalized model that takes into account sensor nonlinearities. Nevertheless, PRNU continues to be used in practice, neglecting the aforementioned details.…”

Section: Introductionmentioning

confidence: 99%

A Stress Test for Robustness of Photo Response Nonuniformity (Camera Sensor Fingerprint) Identification on Smartphones

Martín-Rodríguez

Isasi-de-Vicente

Fernandez-Barciela

2023

Sensors

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In the field of forensic imaging, it is important to be able to extract a camera fingerprint from one or a small set of images known to have been taken by the same camera (or image sensor). Note that we are using the word fingerprint because it is a piece of information extracted from images that can be used to identify an individual source camera. This technique is very important for certain security and digital forensic situations. Camera fingerprint is based on a certain kind of random noise present in all image sensors that is due to manufacturing imperfections and is, thus, unique and impossible to avoid. Photo response nonuniformity (PRNU) has become the most widely used method for source camera identification (SCI). In this paper, a set of attacks is designed and applied to a PRNU-based SCI system, and the success of each method is systematically assessed both in the case of still images and in the case of video. An attack method is defined as any processing that minimally alters image quality and is designed to fool PRNU detectors or, in general, any camera fingerprint detector. The success of an attack is assessed as the increment in the error rate of the SCI system. The PRNU-based SCI system was taken from an outstanding reference that is publicly available. Among the results of this work, the following are remarkable: the use of a systematic and extensive procedure to test SCI methods, very thorough testing of PRNU with more than 2000 test images, and the finding of some very effective attacks on PRNU-based SCI.

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Section: Introductionmentioning

confidence: 99%