@article{2069,
  author = {Nordiana Rahim},
  title = { Source Camera Identification in Online Social Network},
  journal = {Journal of Data Processing},
  year = {2016},
  volume = {6},
  number = {2},
  doi = {},
  url = {},
  abstract = {The online social network is becoming more and more advance now a day. Most of the online users are intent to share their information, especially photo through OSN application. Currently, there is a lot of research on Digital Image that focusing on source identification and forgery detection. This paper is focusing on analyzing the source camera identification in Online Social Network. The techniques consist of sensor imperfection that carries an abundance of information. It is reliable for identification purposes since the digital camera has its own uniquely sensor. Our proposed framework consists of techniques used for extracting the sensor noise from the digital images and then the feature extraction method is applied to extract the image feature. In this framework, Gaussian filter is used to obtain the noisy images. This noisy image is then used for the feature extraction of several texture features. Based on this idea, the extracted features taken from images are then applied to a classifier for identifying source camera. All datasets are analyzed Multilayer Perceptron. The experimental result shows that the best performance of the identification process by combining 4 texture features was achieved with an average accuracy 80%.},
}