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Digital Image Forensics via Intrinsic Fingerprints

机译:通过内在指纹数字图像取证

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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:近几十年来,数字成像经历了巨大的增长,数码相机图像已在越来越多的应用中使用。通过这种越来越普遍和低成本的图像编辑软件的可用性,无法再拍摄数字图像内容的完整性。本文介绍了一种新方法,用于数码相机图像的法医分析。所提出的方法基于观察:在内部和外部采集设备中,在数字图像上留下不同的内在迹线,并且可以识别并采用这些内部指纹的不同内在迹线,以验证数字数据的完整性。可以通过详细的成像模型及其分量分析估计各种相机处理操作的内在指纹。应用于相机捕获图像的进一步处理被建模为操纵滤波器,其施加盲解卷积技术以获得线性时间不变近似,并估计与这些后剖面操作相关联的内部指纹。从测试图像中没有相机施加的指纹表示测试图像不是相机输出,并且可能由其他图像生产过程产生。估计的相机施指纹或新类型的指纹的任何变更或不一致表明,在初始捕获之后,图像在初始捕获之后经历了某种处理,例如篡改或隐写嵌入。通过分析和广泛的实验研究,本文展示了拟议的非流体数字图像取证框架的有效性。

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