A leak in PRNU based source identification? Questioning fingerprint uniqueness

Photo Response Non Uniformity (PRNU) is considered the most effective trace for the image source attribution task. Its uniqueness ensures that the sensor pattern noises extracted from different cameras are strongly uncorrelated, even when they belong to the same camera model. However, with the advent of computational photography, most recent devices of the same model start exposing correlated patterns thus introducing the real chance of erroneous image source attribution. In this paper, after highlighting the issue under a controlled environment, we perform a large testing campaign on Flickr images to determine how widespread the issue is and which is the plausible cause. To this aim, we tested over $240000$ image pairs from $54$ recent smartphone models comprising the most relevant brands. Experiments show that many Samsung, Xiaomi and Huawei devices are strongly affected by this issue. Although the primary cause of high false alarm rates cannot be directly related to specific camera models, firmware nor image contents, it is evident that the effectiveness of PRNU-based source identification on the most recent devices must be reconsidered in light of these results. Therefore, this paper is to be intended as a call to action for the scientific community rather than a complete treatment of the subject.