Digital Forensic Methods Using Systematic Artifacts of Imaging

使用系统成像伪影的数字取证方法

• 批准号: 0830528
• 负责人: Jessica Fridrich
• 金额: $ 30万
• 依托单位: SUNY at Binghamton
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0830528&HistoricalAwards=false
• 关键词: Digital; Forensic; Methods; Using; Systematic

Abstract:The objective of this project is to develop novel digital forensic techniques and support it with experimental validation for later technology transfer to forensic investigators. The goal of digital forensics is to establish the origin, integrity, processing history, and meaning of evidence in digital form that includes digital images, video, or audio. This is an emerging and rapidly developing field typically approached using methods from signal processing, estimation, and detection combined with machine learning. The main thrust of this project is development of forensic methods that rely on systematic artifacts of imaging sensors due to sensor design, in-camera signal processing, and imperfections of the sensor manufacturing process itself. These artifacts form an equivalent of a digital sensor fingerprint. By detecting the fingerprint in a digital image, one can link a given image to the specific camera/sensor that took it and establish thus the image origin and integrity or uncover the image processing history. Some of the research directions are highly relevant and complex problems that have not been addressed before, such as the possibility to detect attempts to forge the fingerprint. Other tasks involve using existing concepts in a novel manner or substantially improve upon existing technology. One of them is to group images according their source camera without having the cameras. The developed methods are subject to large scale experimental verification on a hundred thousand images obtained from more than 1000 cameras.

摘要：该项目的目标是开发新型数字取证技术，并通过实验验证为其提供支持，以便以后将技术转让给取证调查人员。数字取证的目标是确定数字形式证据（包括数字图像、视频或音频）的起源、完整性、处理历史和含义。这是一个新兴且快速发展的领域，通常使用信号处理、估计和检测与机器学习相结合的方法来实现。该项目的主要目标是开发取证方法，这些方法依赖于由于传感器设计、相机内信号处理以及传感器制造过程本身的缺陷而导致的成像传感器的系统伪影。这些伪影相当于数字传感器指纹。通过检测数字图像中的指纹，可以将给定图像链接到拍摄该图像的特定相机/传感器，从而确定图像来源和完整性或揭示图像处理历史。 一些研究方向是以前从未解决过的高度相关且复杂的问题，例如检测伪造指纹企图的可能性。其他任务涉及以新颖的方式使用现有概念或对现有技术进行实质性改进。其中之一是根据源相机对图像进行分组，而无需使用相机。 所开发的方法需要对从 1000 多个摄像机获得的十万张图像进行大规模实验验证。