Source Camera Identification Using Sensor Pattern Noise in Digital Photographs
DOI:
https://doi.org/10.22517/23447214.24829Keywords:
Sensor Pattern Noise (SPN), Source Camera Identification (SCI), Support Vector Machines (SVM), Undecimated Wavelet Transform (UWT).Abstract
At present it is allowed to present digital evidence as evidence in judicial investigations, but at the same time the proliferation of editing programs can skew the information provided by the device that captured the evidence.
In computer forensics, normally for source camera identification (SCI), the sensor noise pattern (SPN) is proposed, on which this investigation was focused, where the objective was to implement and evaluate techniques to face the SCI problem with the SPN using the Non-Decimated Wavelet Transform (UWT). For the implementation of this technique, bright field photographs were used and noise extraction from dark frame photographs was also proposed in order to compare accuracy and training time in each background in which the extraction and filtering of characteristics was carried out. In the space of frequencies by means of the Wavelet Transform not Decimated (UWT) and a Wiener filter, which allows to obtain the fingerprint of the sensor and thus carry out a multiclass analysis by means of classification with vector support machines (SVM) with which obtained accuracy values greater than 95% and an average training time of less than 1586 seconds.
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