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Image source acquisition identification of mobile devices based on the use of features

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Abstract

Nowadays, forensic analysis of digital images is especially important, given the frequent use of digital cameras in mobile devices. The identification of the device type or the make and model of image source are two important branches of forensic analysis of digital images. In this paper we have addressed both of these, with an approach based on different types of image features and the classification using support vector machines. The study has mainly focused on images created with mobile devices and as a result, the techniques and features have been adapted or created for this purpose. There have been a total of 36 experiments classified into 5 sets, in order to test different configurations of the techniques. In the configuration of the experiments, the future use of the technique by the forensic analyst in real situations to create experiments with high technical requirements was taken into account, amongst other things.

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Acknowledgments

Part of the computations of this work were performed in EOLO, the HPC of Climate Change of the International Campus of Excellence of Moncloa, funded by MECD and MICINN.

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Authors and Affiliations

  1. Group of Analysis, Security and Systems (GASS), Department of Software Engineering and Artificial Intelligence (DISIA), Faculty of Computer Science and Engineering, Office 431, Universidad Complutense de Madrid (UCM), Calle Profesor José García Santesmases, 9, Ciudad Universitaria, 28040, Madrid, Spain

    Ana Lucila Sandoval Orozco, Jocelin Rosales Corripio & Luis Javier García Villalba

  2. School of Computing, Office S129A, University of Kent, Cornwallis South Building, Canterbury, CT2 7NF, UK

    Julio César Hernández Castro

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  1. Ana Lucila Sandoval Orozco
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  2. Jocelin Rosales Corripio
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  3. Luis Javier García Villalba
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Correspondence to Luis Javier García Villalba.

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Sandoval Orozco, A.L., Corripio, J.R., García Villalba, L.J. et al. Image source acquisition identification of mobile devices based on the use of features. Multimed Tools Appl 75, 7087–7111 (2016). https://doi.org/10.1007/s11042-015-2633-2

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