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Weighted stego-image steganalysis for JPEG covers

by Rainer Böhme - INFORMATION HIDING. LNCS 5284 , 2008
"... This paper contains two new results for the quantitative detector of LSB replacement steganography based on a weighted stegoimage (WS). First, for spatial domain steganalysis, a variant of the WS method is known to be highly accurate only when cover images have never been subject to lossy compress ..."
Abstract - Cited by 15 (2 self) - Add to MetaCart
compression. We propose a new variant of WS which increases the accuracy for JPEG pre-processed covers by one order of magnitude, thus leaving behind the best structural detectors which were known to be more robust on JPEG pre-compressed covers than WS. Second, we explain why WS-like estimators can also

Steganalysis of JPEG Images: Breaking the F5 Algorithm

by Jessica Fridrich, Miroslav Goljan, Dorin Hogea - in 5th International Workshop on Information Hiding , 2002
"... Abstract. In this paper, we present a steganalytic method that can reliably detect messages (and estimate their size) hidden in JPEG images using the steganographic algorithm F5. The key element of the method is estimation of the cover-image histogram from the stego-image. This is done by decompress ..."
Abstract - Cited by 79 (5 self) - Add to MetaCart
Abstract. In this paper, we present a steganalytic method that can reliably detect messages (and estimate their size) hidden in JPEG images using the steganographic algorithm F5. The key element of the method is estimation of the cover-image histogram from the stego-image. This is done

IMAGE TRANSMORPHING WITH JPEG

by Lin Yuan, Touradj Ebrahimi
"... Picture-related applications are extremely popular because pictures present attractive and vivid information. Nowadays, people record everyday life, communicate with each other, and enjoy entertainment using various interesting imaging applications. In many cases, processed images need to be re-cove ..."
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version while preserving sufficient information about the original image in the processed im-age. It does this by inserting partial information about the original image in the application markers of the processed JPEG image file, so that the original image can be later re-covered. Experiments

Steganalysis Based on JPEG Compatibility

by Jessica Fridrich *a, Miroslav Goljan B, Rui Du B
"... In this paper, we introduce a new forensic tool that can reliably detect modifications in digital images, such as distortion due to steganography and watermarking, in images that were originally stored in the JPEG format. The JPEG compression leaves unique fingerprints and serves as a “fragile water ..."
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, we strongly recommend avoiding using images that have been originally stored in the JPEG format as cover-images for spatial-domain steganography.

Steganalysis Based on JPEG Compatibility

by Miroslav Goljanb, Rui Dub
"... In this paper, we introduce a new forensic tool that can reliably detect modifications in digital images, such as distortion due to steganography and watermarking, in images that were originally stored in the JPEG format. The JPEG compression leaves unique fingerprints and serves as a “fragile water ..."
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, we strongly recommend avoiding using images that have been originally stored in the JPEG format as cover-images for spatial-domain steganography.

Feature-based steganalysis for JPEG images and its implications for future design of steganographic schemes

by Jessica Fridrich - in Proc. Inf. Hiding Workshop, Springer LNCS
"... Abstract. In this paper, we introduce a new feature-based steganalytic method for JPEG images and use it as a benchmark for comparing JPEG steganographic algorithms and evaluating their embedding mechanisms. The detection method is a linear classifier trained on feature vectors corresponding to cove ..."
Abstract - Cited by 110 (13 self) - Add to MetaCart
Abstract. In this paper, we introduce a new feature-based steganalytic method for JPEG images and use it as a benchmark for comparing JPEG steganographic algorithms and evaluating their embedding mechanisms. The detection method is a linear classifier trained on feature vectors corresponding

qa-cover (1401x1991x24b jpeg) PREFACE

by unknown authors
"... In this globalised world, higher educational institutions not only have to meet the increasing market demand for people with the ability to work in different crosscultural settings, but also carry with them the mission of nurturing academic excellence and professional advancement. ASEAN must strive ..."
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In this globalised world, higher educational institutions not only have to meet the increasing market demand for people with the ability to work in different crosscultural settings, but also carry with them the mission of nurturing academic excellence and professional advancement. ASEAN must strive for quality assurance networking development as a mechanism to reach and maintain a high standard education, not just for one particular country, but for the ASEAN region as a whole. There have been strong QA movements in ASEAN in recent years in response to the liberalisation of education and the need for standard education. Governments of ASEAN countries have prioritised QA in education as a national agenda. Individual universities set up their own quality criteria, partly in consultation with other institutions at the national and international levels. At the regional level, the ASEAN University Network’s initiative for the establishment of binding QA standards among its member universities represents a pioneering move. The ASEAN University Network’s efforts to set up a standard quality assurance system originated from the need to improve quality amid globalisation, realising that the fastest way for us to grow is to start a long QA journey together. The creation of the ASEAN University Network-Quality Assurance (AUN-QA) was initiated in 1998 by the first Chairman of the AUN Board of Trustees (AUN-BOT), Professor Dr. Vanchai Sirichana, who believes that it will help all higher education institutions in ASEAN attain and maintain their high standard of education. And in the highly competitive, globalised world of education, quality assurance helps bridge the gaps among individual institutions with diverse cultures and resources.

New Features for Specific JPEG Steganalysis

by unknown authors
"... Abstract — We present in this paper a new approach for specific JPEG steganalysis and propose studying statistics of the compressed DCT coefficients. Traditionally, steganographic algorithms try to preserve statistics of the DCT and of the spatial domain, but they cannot preserve both and also contr ..."
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Abstract — We present in this paper a new approach for specific JPEG steganalysis and propose studying statistics of the compressed DCT coefficients. Traditionally, steganographic algorithms try to preserve statistics of the DCT and of the spatial domain, but they cannot preserve both and also

Compressed Domain Processing of JPEG-encoded images

by Brian C. Smith, Lawrence A. Rowe - Real-Time Imaging , 1996
"... This paper addresses the problem of processing motion-JPEG video data in the compressed domain. The operations covered are those where a pixel in the output image is an arbitrary linear combination of pixels in the input image, which includes convolution, scaling, rotation, translation, morphing, de ..."
Abstract - Cited by 22 (4 self) - Add to MetaCart
This paper addresses the problem of processing motion-JPEG video data in the compressed domain. The operations covered are those where a pixel in the output image is an arbitrary linear combination of pixels in the input image, which includes convolution, scaling, rotation, translation, morphing

Steganalysis of JPEG Images Using Rich Models

by Jan Kodovský, Jessica Fridrich
"... In this paper, we propose a rich model of DCT coefficients in a JPEG file for the purpose of detecting steganographic embedding changes. The model is built systematically as a union of smaller submodels formed as joint distributions of DCT coefficients from their frequency and spatial neighborhoods ..."
Abstract - Cited by 21 (14 self) - Add to MetaCart
covering a wide range of statistical dependencies. Due to its high dimensionality, we combine the rich model with ensemble classifiers and construct detectors for six modern JPEG domain steganographic schemes: nsF5, model-based steganography, YASS, and schemes that use side information at the embedder
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