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Photo Response Non-Uniformity (PRNU) has been used as a powerful devicefingerprint for image forgery detection because image forgeries can be revealedby finding the absence of the PRNU in the manipulated areas. The correlationbetween an image's noise residual with the device's reference PRNU is oftencompared with a decision threshold to check the existence of the PRNU. A PRNUcorrelation predictor is usually used to determine this decision thresholdassuming the correlation is content-dependent. However, we found that not onlythe correlation is content-dependent, but it also depends on the camerasensitivity setting. \textit{Camera sensitivity}, commonly known by the name of\textit{ISO speed}, is an important attribute in digital photography. In thiswork, we will show the PRNU correlation's dependency on ISO speed. Due to suchdependency, we postulate that a correlation predictor is ISO speed-specific,i.e. \textit{reliable correlation predictions can only be made when acorrelation predictor is trained with images of similar ISO speeds to the imagein question}. We report the experiments we conducted to validate the postulate.It is realized that in the real-world, information about the ISO speed may notbe available in the metadata to facilitate the implementation of our postulatein the correlation prediction process. We hence propose a method calledContent-based Inference of ISO Speeds (CINFISOS) to infer the ISO speed fromthe image content.

On Addressing the Impact of ISO Speed upon PRNU and Forgery Detection