Unsupervised Classification of Mobile Device Images

As mobile devices are seeing widespread usage in the everyday life, the images from mobile devices can be used as evidence in legal purposes. Accordingly, the identification of mobile devices images are of significant interest in digital forensics. In this paper, we propose a method to determine the mobile devices camera source based on the grouping or clustering of images according to their source acquisition. Our clustering technique does not involve a priori knowledge of the number of images or devices to be identified or training data for a future classification stage. The proposal combines of hierarchical and flat clustering and the use of sensor pattern noise. Experimental results show that our approach is very promising for identifying mobile devices source.