Open AccessSmartphone image acquisition forensics using sensor fingerprint
Author(s) -
Sandoval Orozco Ana Lucila,
García Villalba Luis Javier,
Arenas González David Manuel,
Corripio Jocelin Rosales,
HernandezCastro Julio,
Gibson Stuart James
Publication year - 2015
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2014.0243
Subject(s) - computer science , artificial intelligence , computer vision , digital forensics , fingerprint (computing) , set (abstract data type) , digital image , identification (biology) , noise (video) , wavelet , fingerprint recognition , pattern recognition (psychology) , image processing , image (mathematics) , computer forensics , computer security , botany , biology , programming language
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.