Smartphone image acquisition forensics using sensor fingerprint

The forensic analysis of digital images from mobile devices is particularly important given their quick expansion and everyday use in the society. A further consequence of digital images´ widespread use is that they are used today as silent witnesses in legal proceedings, as crucial evidence of the crime. This study specifically addresses the description of a technique that allows the identification of the image source acquisition, for the specific case of mobile devices images. This approach is to extract wavelet-based features from sensor pattern noise which are then classified using a support vector machine. Moreover, there are a number of parameters that allows the authors to adapt the execution of the algorithm to specific situations desired for the forensic analyst (a variety of types and sizes of image or optimising the average accuracy rate in terms of processing time). This article describes a set of experiments with the same set of images that can obtain general conclusions for the different configurations.