论文标题
使用深度学习的数字图像取证
Digital Image Forensics using Deep Learning
论文作者
论文摘要
在对犯罪活动进行调查期间，目前的问题是确定视频的信誉并确定视频是真实的。如今，验证素材的一种方法是确定用于捕获相关图像或视频的相机。虽然一种非常常见的方法是使用图像元数据，但可以通过更改视频内容或甚至将两个不同摄像机的内容拼接在一起来轻松伪造这些数据。考虑到针对此问题提出的多种解决方案，尚未得到充分解决。我们项目的目的是构建一种算法，该算法可以使用哪些相机用于使用图像中本质上留下的信息的痕迹（使用过滤器）捕获图像，然后在这些过滤器上进行深层神经网络。解决此问题将对犯罪和民事审判甚至新闻报道中使用的证据的验证产生重大影响。
During the investigation of criminal activity when evidence is available, the issue at hand is determining the credibility of the video and ascertaining that the video is real. Today, one way to authenticate the footage is to identify the camera that was used to capture the image or video in question. While a very common way to do this is by using image meta-data, this data can easily be falsified by changing the video content or even splicing together content from two different cameras. Given the multitude of solutions proposed to this problem, it is yet to be sufficiently solved. The aim of our project is to build an algorithm that identifies which camera was used to capture an image using traces of information left intrinsically in the image, using filters, followed by a deep neural network on these filters. Solving this problem would have a big impact on the verification of evidence used in criminal and civil trials and even news reporting.
