Defending Against Statistical Steganalysis

By Niels Provos. USENIX Security Symposium, 2001

724 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/fdf2ee8db451b34f6a0100b833cac960047b8e90

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Jessica J. Fridrich
2. Tomás Pevný
3. Jan Kodovský
4. Bin Li
5. Hany Farid
6. Vojtech Holub
7. Y. Shi
8. Jiwu Huang

Citations in the corpus

• LINGUISTIC STEGANOGRAPHY: SURVEY, ANALYSIS, AND ROBUSTNESS CONCERNS FOR HIDING INFORMATION IN TEXT (2004, background): “Steganalysis, then, is generally considered to be successful when the existence of a message is detected (Zöllner et al: 344, Provos 2001: 1).”
• Detecting Hidden Messages Using Higher-Order Statistics and Support Vector Machines (2002, methodology): “Unique to OutGuess is a technique for embedding into only one-half of the redundant bits and then using the remaining redundant bits to preserve the first-order distribution of DCT coefficients [16].”
• Steganalysis of JPEG Images: Breaking the F5 Algorithm (2002, methodology): “This paradigm can be adapted not only to raw formats but also to palette images after pre-sorting the palette (EZ Stego [10]) and to JPEG images (J-Steg [10], JP Hide&Seek [10], and OutGuess [11]).”
• Feature-Based Steganalysis for JPEG Images and Its Implications for Future Design of Steganographic Schemes (2004, methodology): “In Section 3, we give the details of the detection scheme and discuss the experimental results for OutGuess [11], F5 [13], and Model Based Steganography [12,14].”
• Detecting hidden messages using higher-order statistical models (2002, methodology): “Unique to OutGuess is a technique for embedding into only one-half of the redundant bits and then using the remaining redundant bits to preserve the first-order distribution of DCT coefficients [ 12 ].”
• Statistically undetectable jpeg steganography: dead ends challenges, and opportunities (2007, methodology): “3.1 Statistics-preserving steganography(Steghide, Model Based Steganography) We did not include in our list OutGuess [30] and other methods that use statistical restoration [35] as they are typ­ically highly detectable.”
• Image Steganography and Steganalysis: Concepts and Practice (2003, methodology): “A second technique proposed by Fridrich [6] deals with the Outguess [21] embedding program.”
• Invisible Backdoor Attacks on Deep Neural Networks Via Steganography and Regularization (2019, background): “Steganography is a type of covert communication technology [25].”
• A Markov Process Based Approach to Effective Attacking JPEG Steganography (2006, methodology): “In this paper we look at three recent published and most advanced steganographic methods, i.e., Outguess [2], F5 [1], and the model-based steganography (MB) [3].”
• Detection of Double-Compression in JPEG Images for Applications in Steganography (2008, methodology): “Second, some steganographic algorithms (Jsteg, F5 [18], OutGuess [14]) always decompress the cover JPEG image into the spatial domain before embedding.”
• Model-Based Steganography (2003, methodology): “A number of methods have been proposed for hiding messages in digital media including JPEG images, and MP3 audio files[8, 12, 9 ].”
• Benchmarking for Steganography (2008, methodology): “As an example, we cite the successful attacks [32] on steganographic systems that preserve first order statistics of DCT coefficients in JPEG images [33, 29, 19, 10, 39].”
• A Survey on Image Steganography and Steganalysis (2011, methodology): “OutGuess[31] is provided by Provos as UNIX source code.”