![]() ![]() For example, an approach worth mentioning is surely the one proposed by J. However, in order to improve the capacity of detection of information hidden through F5, we can approach the problem in a different way. However, it is important to remember that it strongly minimizes the number of DTC coefficients needed to store the secret information, consequently reducing the changes that occur in the cover image.įor these features, the F5 has a good resistance also against statistical attacks. The specific discussion of this fairly complex algorithm is beyond the scope of this article. The use of so-called Matrix Encoding (useful for improving the efficiency of embedding, significantly decreasing the proportion of alterations needed to embed hidden data within an image). Method that is not only much more complex than the JSteg, but even with respect to its predecessor (the F4, not treated here). This peculiarity is mainly due to the fact that the data to be hidden is inserted consequentially within DTC coefficients, and not in pseudo-random order (or, more simply, “scattered”), causing evident statistics alterations that are visible in the histogram of the frequencies of the DTC coefficients. Although this method ensures effective protection against visual attacks, it is quite vulnerable to statistical attacks. Anyone who knows it can recover the hidden message. Replace LSB of DTC with bit of data to be hiddenĪs is easily observable, the algorithm does not make use of an input secret key to share with whom you want to read the hidden message ( stego-key). Below, for a clearer understanding of this algorithm, is a representation through simplified pseudo-code: However, because changes occur in the frequency domain rather than in the spatial domain, JSteg is not susceptible to visual attacks mentioned above. It’s useful to note that the modification of a single DTC coefficient expands on all 64 pixels in the block. The JSteg exploits the LSB of DTC coefficients as redundant bits to insert hidden content within a cover media. It’s with elimination of these areas that the compression algorithm is so efficient. The areas represented by a greater density of white pixels are those with higher frequencies that are not perceptible by the human eye, and are therefore expendable. An 8×8 pixel block is more simplistically converted in a frequency spectrum formed only by pixels in black and white. This formula represents the transformation of a Canonical Base belonging to a spatial domain in a corresponding 8×8 block belonging to the frequencies domain. Normally, 8×8 pixels of each block are transformed with the following formula: To explain what DTC is, we need to keep in mind that for each color component of an image, the JPEG format makes use of a mathematical function called Discrete Cosine Transformation, or simply DTC, in order to convert 8×8 pixel blocks (called also Canonical Bases) of an image in 64 corresponding DTC coefficients. To better understand this, we need a quick explanation about DTC. Its working routine does nothing more than consequentially replace the LSBs of DTC coefficients with bits of the data to be hidden. It is absolutely the first algorithm of its kind and perhaps it’s also the most used. Only by doing so can one be sure of maintaining that state of mind known as a burning desire to win - essential to success.The Jsteg is one of the most classical steganographic algorithms used. Every person who wins in any undertaking must be willing to cut all sources of retreat. ![]()
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