Real or Fake? A Practical Method for Detecting Tempered Images

Abstract

Tempering images has become technology that almost everyone can complete, including fake news, fake evidence presented in court, or forged documents. The main reason is because these editing tools, such as Photoshop, is simple to use, which is an urgent issue we need to solve. Hence, automatic tools helping to find manipulated images apart is critical for fighting misinformation campaigns. Here we propose and evaluate a neural network-based method. It can detect whether images have been artificially modified (classification), and further indicate the forged parts (segmentation). Our proposed method has better performance than most baseline methods. Last but not least, our method is not only effective on JPEG format, but can also be used on other formats.