![]() used χ 2 testing to recover the stego key of LSB steganography if the carrier is unknown. proposed three attack algorithms to recover the stego key of LSB steganography if the carrier is known or reused. (3) In the case of that the investigator knows the embedding position generator, Zhang et al. fused spatial and wavelet filtering results to locate the modified pixels of LSB matching steganography. (2) In the case of that the investigator owns a single stego image, in 2012, Quach proved that the modified pixels in a stego image can be located with a lower error rate if enough independent non-random discriminant functions can be used. proposed a payload locating method based on co-frequency sub-image filtering for a category of pseudo-random JPEG image steganography, such as JSteg and F5 steganography. ![]() proposed a locating methodology based on quantitative steganalysis for this case. In 2014, Quach used the residuals to estimate the rough sequence of stego positions when owning enough stego images embedded messages of different sizes along the same path. Subsequently, a series of payload locating steganalysis algorithms were proposed for spatial LSB steganography. (1) In the case of that the investigator owns multiple stego images with messages embedded into the same positions, Ker first proposed to locate the payload of LSB (least significant bit) replacement by averaging the weighted stego-image residuals in the same positions. In recent years, some steganalysis techniques that can locate and even extract the hidden message, also referred to as the payload, have been reported for the following four cases. Existing steganalysis researches mainly focus on detecting stego objects, but investigators are more interested in extracting the hidden secret information. In contrast, steganalysis is the technique of detecting stego objects, extracting or removing the message embedded by steganography. So far, many steganography algorithms have been proposed for different types of covers. Experimental results show that the proposed method can recover the stego key accurately and efficiently, even when the existing Xu’s method fails for the high or very low embedding ratio.ĭigital steganography is the art of hiding messages in redundant parts of digital media such as images, video, and audio for the purpose of covert communication. ![]() Additionally, the cardinality of the shuffling key space is significantly reduced by examining the extracted encoding parameter and message length. The shuffling key is then recovered based on the distribution difference between the bit sequences extracted by the true and false shuffling keys. Firstly, the check matrix is recovered based on the embedding ratio estimated by quantitative steganalysis. Therefore, this paper proposes a method for recovering the stego key of a typical JPEG (Joint Photographic Experts Group) image steganography-F5 which composes of the check matrix and shuffling key. When embedding secret message into image by steganography with matrix encoding, there are still no effective methods to recover the stego key because it is difficult to statistically distinguish the stego coefficient sequences selected by true and false keys. ![]()
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