Source Smartphone Identification Using Sensor Pattern Noise and Wavelet Transform

The ability to identify the source camera for an image has application

in the areas of digital forensics and multimedia data

mining. The majority of previous research in this area has focused

on primary function imaging devices (i.e. digital cameras).

In this work we use the pattern noise of an imaging

sensor to classify digital photographs according to the source

smartphone from which they originated. This is timely work

as new smartphone models large imaging sensors, affording

significant improvements in classification rates using pattern

noise. Our approach is to extract wavelet based features which

are then classified using a support vector machine. We show

that this method generalises well when the number of source

cameras is increased.