Smartphone image clustering

Abstract

Every day the use of images from mobile devices as evidence in legal proceedings is more usual and common.Image source acquisition identification is a branch of digital forensic analysis.We use a combination of hierarchical and flat clustering and the use of Sensor Pattern Noise for source identification.We make a series of experiments which emulate similar situations to those that may occur in reality. Every day the use of images from mobile devices as evidence in legal proceedings is more usual and common. Therefore, forensic analysis of mobile device images takes on special importance. This paper explores the branch of forensic analysis which is based on the identification of the source, specifically on the grouping or clustering of images according to their source acquisition. In contrast with other state of the art techniques for source identification, hierarchical clustering does not involve a priori knowledge of the number of images or devices to be identified or training data for a future classification stage. That is, a grouping by classes with all the input images is performed. The proposal is based on the combination of hierarchical and flat clustering and the use of Sensor Pattern Noise (SPN). There has been a series of experiments which emulate similar situations to those that may occur in reality to test the robustness and reliability of the results of the technique. The results are satisfactory in all the experiments, obtaining high rates of success.