Source camera identification is the procedure of finding out which camera model has been used to capture an image.
In the past few years, there has been a high-speed growth of research interest in the field of forensics. In our present work, we
have proposed a Deep Learning approach for identifying the camera model of ten cameras as a part of the Camera Model
Identification Challenge organized by the Kaggle.com. Through this paper, we have presented a camera model identification
method based on Convolutional Neural Network (CNN). In contrast to traditional methods, CNNs can spontaneously and
concurrently extricate features and can be trained to classify during the learning process. Source camera identification is used in
legal as well as security matters as a proof. As a correlation to previous task, researchers have suggested to utilize the artifacts
that are present in the pipeline of camera to gather particular features manually and use them to differentiate between individual
devices or camera models.
