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Digital Image Forensics via Intrinsic Fingerprints

机译:通过固有指纹进行数字图像取证

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摘要

Digital imaging has experienced tremendous growth in recent decades, and digital camera images have been used in a growing number of applications. With such increasing popularity and the availability of low-cost image editing software, the integrity of digital image content can no longer be taken for granted. This paper introduces a new methodology for the forensic analysis of digital camera images. The proposed method is based on the observation that many processing operations, both inside and outside acquisition devices, leave distinct intrinsic traces on digital images, and these intrinsic fingerprints can be identified and employed to verify the integrity of digital data. The intrinsic fingerprints of the various in-camera processing operations can be estimated through a detailed imaging model and its component analysis. Further processing applied to the camera captured image is modelled as a manipulation filter, for which a blind deconvolution technique is applied to obtain a linear time-invariant approximation and to estimate the intrinsic fingerprints associated with these postcamera operations. The absence of camera-imposed fingerprints from a test image indicates that the test image is not a camera output and is possibly generated by other image production processes. Any change or inconsistencies among the estimated camera-imposed fingerprints, or the presence of new types of fingerprints suggest that the image has undergone some kind of processing after the initial capture, such as tampering or steganographic embedding. Through analysis and extensive experimental studies, this paper demonstrates the effectiveness of the proposed framework for nonintrusive digital image forensics.
机译:在最近的几十年中,数字成像经历了巨大的增长,并且数字照相机图像已用于越来越多的应用中。随着这种日益普及和低成本图像编辑软件的可用性,数字图像内容的完整性不再被视为理所当然。本文介绍了一种用于数码相机图像取证分析的新方法。所提出的方法是基于以下观察:在采集设备内部和外部的许多处理操作都会在数字图像上留下明显的固有痕迹,并且可以识别这些固有指纹并将其用于验证数字数据的完整性。可以通过详细的成像模型及其组件分析来估计各种相机内部处理操作的固有指纹。应用于相机捕获图像的进一步处理被建模为操作过滤器,为此对其应用了盲反卷积技术以获得线性时不变近似值并估计与这些相机后操作相关的固有指纹。测试图像中没有相机施加的指纹表明该测试图像不是相机输出,可能是由其他图像生成过程生成的。估计的相机施加的指纹之间的任何更改或不一致,或者存在新类型的指纹,都表明图像在初始捕获后已进行了某种处理,例如篡改或隐匿性嵌入。通过分析和广泛的实验研究,本文证明了所提出的非侵入式数字图像取证框架的有效性。

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