Image origin identification for online social networks (OSNs)
Weiwei Sun, Jiantao Zhou · 2017
The rapid development of various online social networks (OSNs) makes it unprecedentedly popular to share photos online. This leads OSNs one of the main provenances of online images. However, the illegal activities on these online contents such as misusing and dissemination widely exist. Under this circumstance, the identification of the origin and the propagation path of an online image is crucial for many forensic applications. In this work, we propose a simple yet effective method to determine the image origin by exploiting the unique traces left by the operations of different OSNs. To this end, we first conduct a comprehensive study on the manipulations that various OSNs perform on uploaded images. Based on the knowledge of these operations, we design a feature vector and eventually train a SVM classifier for identifying where these online images come from. Extensive experimental results are provided, showing that the proposed method achieves very high accuracy of image origin identification, and outperforms the state-of-the-art work.