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Improved Stego Sensitivity Measure for ± A Steganalysis

机译:改进的sego敏感度量±steganysis

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This article addresses four basic goals; 1) the evaluation of sequentially and randomly embedded stego evidence within digital images 2) the identification of "steganographic fingerprint" for special domain based steganographic methods, 3) the reduction of Steganalysis false detection rate, and 4) the investigation of two well known pixel comparison based Steganalysis methods. We present an improved version of Stego Sensitivity Measure, which is based on the statistics of sample pair (the basic unit), rather than individual samples which is very sensitive to ± A embedding. The presented measure enhances stego detection accuracy and localization of stego areas within sequentially and randomly embedded color or gray scale stego images. In addition, it estimates the message length of an embedded bit-stream within bit planes of a digital image, and it has better localization of steganography detected along with an improved estimation of the message length. It also identifies the "steganographic fingerprint" of special domain sequentially and randomly based steganographic methods. Numerical experimentation was conducted with an arbitrary image database of 200 color TIFF and RAW images taken with the Nikon D100 and the Canon EOS Digital Rebel cameras. In this article comparison are also shown using two known Steganalysis methods Raw Quick Pairs and RS Steganalysis which have revealed that; a) The false alarm rate for the proposed detection method is p = 0.9 for a database of 200 images clean images while RS Steganalysis has shown a high false alarm rate for clean images of p = 2.8. b) The two methods Raw Quick Pairs and RS Steganalysis cannot be used for localization of steganographic regions due to the statistical properties of the detection methods.
机译:本文将讨论四个基本目标; 1)的顺序和随机地嵌入隐秘证据的数字图像内的评价2)“的隐写指纹”的标识为特殊域基于隐写方法,3)隐写错误检测率的降低,和4)两种熟知像素的调查比较基于隐写分析方法。我们提出隐写灵敏度测量,这是基于样品对统计信息(基本单元),而不是单个样品的改进版本,这是到±A嵌入非常敏感。所提出的措施提高隐秘检测精度和顺序和随机地嵌入彩色或灰度图像隐秘内隐写区域的定位。此外,它估计的数字图像的位平面内的嵌入比特流的消息长度,并且其具有与该消息长度的改进的估计检测到的沿的隐写术更好定位。它还确定的特殊顺序域和随机基于隐写方法中的“隐写指纹”。数值实验用的尼康D100和佳能EOS数码叛军相机拍摄的200个色TIFF和RAW图像的任意图像数据库进行。在本文中使用的比较两种已知的隐写方法生快速对和RS隐写已经揭示,也被示出; a)用于所提出的检测方法中的虚警率是用于同时RS隐写已经显示出对于p = 2.8的干净图像的高误报警率的200幅图像清洁图像的数据库P = 0.9。 B)这两种方法生快速对和RS隐写不能用于隐写区域的定位由于的检测方法的统计特性。

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