H. Farid, "Detecting steganographic messages in digital images," Tech. Rep. TR2001-412, Dartmouth College. Home/Search Document Details and Download
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Blind Steganography Detection Using a.. - Jackson, Gunsch.. (2002) (Correct)
....can raise suspicion of steganography [9, 23] However, steganography tools such as OutGuess [20] are starting to maintain the first order statistics during the embedding process. Steganalytic techniques using sensitive higher order statistics have been developed to counter this covering of tracks [6, 10]. Farid developed a steganalytic method that uses deviation from expected statistics as an indication of a potential hidden message. The training set for his Fisher linear discriminant (FLD) analysis consisted of a mixture of clean and stego images. He then tested the trained FLD on a previously ....
....for JpegJsteg [22] EzStego [16] and OutGuess. The features that he was training and testing on were based upon particular statistics gathered from a wavelet decomposition of each image. Farid s work will be discussed in more detail later because it will be heavily leveraged in this research. [6] 5 2.3 Research Goal and Hypothesis The goal of this research is to develop CIS classifiers, which will be evolved using a genetic algorithm (GA) that distinguish between clean and stego images by using statistics gathered from a wavelet decomposition. With successful classifiers the ....
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Farid, Hany. Detecting Steganographic Messages in Digital Images . Technical Report TR2001-412, Hanover, NH: Dartmouth College, 2001.
A Fast and Effective Steganalytic Technique against Jsteg-Like.. - Zhang, Ping (2003) (1 citation) (Correct)
.... image quality measures and Farid s approach based on higher order statistics, is a meta detection method in the sense that after training on original and stego images database it can detect the existence of hidden messages embedded using any steganographic method regardless of the embedding domain [7,8]. Such steganalytic algorithms usually find an appropriate set of sensitive statistical quantities with distinguishing capabilities. Clustering algorithms or regression models can then be used to construct a classifier for carrier images and stego images from the collected experimental data. ....
....construct a classifier for carrier images and stego images from the collected experimental data. Universal blind steganalysis algorithms are more flexible because they can be quickly adjusted to new or completely unknown steganalytic methods. However, from the experimental results given in [7] and [8], we know that they are generally less accurate and reliable than those algorithms specifically targeted to a specific steganographic method. In this paper, we propose a fast and effective steganalytic technique based on statistical distributions of DCT coefficients which is aimed at two kinds of ....
H. Farid. Detecting Steganographic Message in Digital Images. Report TR2001-412, Dartmouth College, Hanover, NH, 2001
Detecting Steganographic Content on the Internet - Provos, Honeyman (2001) (15 citations) (Correct)
....bits to be replaced with data from a secret message. The stego medium is created by replacing the selected redundant bits with message bits. The modi cation of redundant bits can change the statistical properties of the cover medium. As a result, statistical analysis may reveal the hidden content [3, 15, 20]. In Section 4, we explain this in detail. 3 Information Hiding in JPEG Images JPEG images are commonly used on Internet web sites. This section brie y explains the JPEG format and how it can be used for information hiding. The JPEG image format uses a discrete cosine transform (DCT) to ....
....increases when hidden messages have been embedded. While they are able to detect steganographic content, they are not able to di erentiate between steganographic systems. Farid nds predictable higher order statistics of unmodi ed images and shows that embedding messages distorts these statistics [3]. To nd predictable higherorder statistics a large training set is required. As a result, the predictable statistics seem to re ect only properties of the sample set and might not apply for all images in general. The methods presented here do not require special training and apply to all images ....
Hany Farid. Detecting Steganographic Messages in Digital Images. Technical Report TR
Kernel Fisher Discriminant for Steganalysis of JPEG Hiding.. - Harmsen, Pearlman (2004) (Correct)
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H. Farid, "Detecting steganographic messages in digital images," Tech. Rep. TR2001-412, Dartmouth College.
Secret Key Estimation in Sequential Steganography - Trivedi, Chandramouli (2005) (Correct)
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H. Farid. Detecting steganographic message in digital images. Technical Report TR2001-412, Dartmouth College, 2001.
Secret Key Estimation in Sequential Steganography - Trivedi (2003) (Correct)
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H. Farid, Detecting steganographic message in digital images, Tech. Report TR2001-412, Dartmouth College, 2001. 42 43
A Communications Approach to Image Steganography - Eggers, Bäuml, Girod (2002) (3 citations) (Correct)
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H. Farid, "Detecting steganographic messages in digital images," tech. rep., Dartmouth College, Computer Science, 2001. TR2001-412.
Practical Steganalysis of Digital Images - State of the Art - Fridrich, Goljan (2002) (9 citations) (Correct)
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H. Farid, "Detecting Steganographic Message in Digital Images", Report TR
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