Abstract-Matrix embedding is a previously introduced coding method that is used in steganography to improve the embedding efficiency (increase the number of bits embedded per embedding change). Higher embedding efficiency translates into better steganographic security. This gain is more important for long messages than for shorter ones because longer messages are in general easier to detect. In this paper, we present two new approaches to matrix embedding for large payloads suitable for practical steganographic schemes-one based on a family of codes constructed from simplex codes and the second one based on random linear codes of small dimension. The embedding efficiency of the proposed methods is evaluated with respect to theoretically achievable bounds.

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In this paper, we introduce a new approach to passive-warden steganography in which the sender embeds the secret message into a certain subset of the cover object without having to share the selection channel with the recipient. An appropriate informationtheoretical model for this communication is writing in memory with (a large number of) defective cells [1]. We describe a simple variable-rate random linear code for this channel (the "wet paper" code) and use it to develop a new steganographic methodology for digital media files -Perturbed Quantization. In Perturbed Quantization, the sender hides data while processing the cover object with an information-reducing operation, such as lossy compression, downsampling, A/D conversion, etc. The sender uses the cover object before processing as side information to confine the embedding changes to those elements of the processed cover object whose values are the most "uncertain". This informed-sender embedding and uninformed-recipient message extraction improves steganographic security because an attacker cannot easily determine from the processed stego object the location of embedding changes. Heuristic is presented and supported by blind steganalysis [2] that a specific case of Perturbed Quantization for JPEG images is significantly less detectable than current JPEG steganographic methods. Categories and Subject Descriptors MOTIVATIONThe primary goal of steganography is to build a statistically undetectable communication channel (the famous Prisoner Problem [3]). In order to embed a secret message, the sender slightly modifies the cover object to obtain the embedded stego object. In steganography under the passive warden scenario [4,5], the goal is to communicate as many bits as possible without introducing any detectable artifacts into the cover object. Attempts to give a formal definition of the concept of steganographic security can be found in [5][6][7][8]. In practice, a steganographic scheme is considered secure if no existing attack can be modified to build a detector that would be able to distinguish between cover and stego images with a success better than random guessing.One possible measure to improve the security of steganographic schemes for digital media is to embed the message in adaptively selected components of the cover object [9-11], such as noisy areas or segments with a complex texture. However, if the adaptive selection rule is public or only "weakly dependent on a key", the attacker can apply the same rule and start building an attack. It is then a valid question whether the adaptive selection improves steganographic security at all. A good example of a scheme where adaptive pixel selection in fact decreased its security is the recent surprising result of Westfeld [12].This problem with adaptive steganography could be remedied if the selection rule was determined from some side information available only to the sender but in principle unavailable to the recipient (and thus any attacker). For example, imagine the situation when the send...

The objective of steganalysis is to detect messages hidden in cover objects, such as digital images. In practice, the steganalyst is frequently interested in more than whether or not a secret message is present. The ultimate goal is to extract and decipher the secret message. However, in the absence of the knowledge of the stego technique and the stego and cipher keys, this task may be extremely time consuming or completely infeasible. Therefore, any additional information, such as the message length or its approximate placement in image features, could prove very valuable to the analyst. In this paper, we present general principles for developing steganalytic methods that can accurately estimate the number of changes to the cover image imposed during embedding. Using those principles, we show how to estimate the secret message length for the most common embedding archetypes, including the F5 and OutGuess algorithms for JPEG, EzStego algorithm with random straddling for palette images, and the classical LSB embedding with random straddling for uncompressed image formats. The paper concludes with an outline of ideas for future research such as estimating the steganographic capacity of embedding algorithms. Basics of steganography and steganalysisThe purpose of steganography is to communicate information in a stealth manner so that anyone who inspects the messages being exchanged cannot collect enough evidence that the messages hide additional secret data. As opposed to cryptography that makes the communication unintelligible to those who do not know the proper cipher keys, steganography makes the communication inconspicuous or invisible. An old example of steganography is writing messages between the lines of an ordinary letter using invisible ink. Another simple technique is to use tiny markers (pinholes) to mark letters in a text. A very well-written historical perspective on steganography can be found in [20]. In today's digital world, invisible ink and paper have been replaced by much more versatile and practical covers for hiding messages -digital documents, images, video, and audio files. All electronic documents containing perceptually irrelevant or redundant information provide a good environment for steganographic communication. The object that holds the secret information is called the cover object. After a secret message has been hidden in the cover, the cover object becomes the stego object.

Abstract-Wet paper codes were previously proposed as a tool for construction of steganographic schemes with arbitrary (non-shared) selection channels. In this paper, we propose a new approach to wet paper codes using random linear codes of small codimension that at the same time improves the embedding efficiency (number of random message bits embedded per embedding change). Practical algorithms are given and their performance is evaluated experimentally and compared to theoretically achievable bounds. An approximate formula for the embedding efficiency of the proposed scheme is derived. The proposed coding method can be modularly combined with most steganographic schemes to improve their security.