29-05-2012, 01:35 PM
SLSB: Improving the Steganographic Algorithm LSB
CIBSI-Dia3-Sesion9(1).pdf (Size: 173.42 KB / Downloads: 152)
Introduction
The steganography can be considered as a branch of cryptography that tries to hide messages within others, avoiding the perception that there is some kind of message. To apply steganographic techniques cover files of any kind can be used, although archives of image, sound or video files are the most used today. Similarly, information to hide can be anything: text, image, video, sound, etc.
There are two trends at the time to implement steganographic algorithms: the methods that work in the spatial domain (altering the desired characteristics on the file itself) and the methods that work in the transform domain (performing a series of changes to the cover image before hiding information. To select the best areas the Discrete Cosine Transform DCT, Wavelet Transform, etc. are used).
While the algorithms that work in the transform domain are more robust, that is, more resistant to attacks, the algorithms that work in the spatial domain are simpler and faster.
The best known steganographic method that works in the spatial domain is the LSB [1] (Least Significant Bit), which replaces the least significant bits of pixels selected to hide the information. This method has several implementation versions that improve the algorithm in certain aspects [2][3][4][5][6][7].
Methods in Spatial Domain
A basic classification of steganographic algorithms operating in the spatial domain as the method for selecting the pixels distinguishes three main types: non-filtering algorithms, randomized algorithms and filtering algorithms.
Non-filtering Algorithm
This is the simplest steganographic method based in the use of LSB, and therefore the most vulnerable. The embedding process consists of the sequential substitution of each least significant bit of the image pixel for each bit of the message. For its simplicity, this method can camouflage a great volume of information [9].
This technique is quite simple. It is necessary only a sequential LSB reading, starting from the first image pixel, to extract the secret message. This method also generates an unbalanced distribution of the changed pixels, because the message is embedded at the first pixels of the image, leaving unchanged the remaining pixels.
Randomized Algorithm
This technique was born as a solution for the problems of the previous method. Each one, the sender and the receiver of the image has a password denominated stego-key that is employed as the seed for a pseudo-random number generator. This creates a sequence which is used as the index to have access to the image pixel. The message bit is embedded in the pixel of the cover image as the index given by the pseudo-random number generator [9].
The two main features of the pseudo-random permutation methods are the use of password to have access to the message, and the well-spread message bits over the image.
Filtering Algorithm
This algorithm filters the cover image by using a default filter and hides information in those areas that get a better rate. The filter is applied to the most significant bits of every pixel, leaving the less significant to hide information. The filter ensures the choice of areas of the image in the least impact with the inclusion of information, which affects a greater difficulty of detecting the presence of hidden messages [10]. The retrieval of information is ensured because the bits used for filtering are not changed, implying that the reapply the filter will select the same bits in the process of concealment. It is the most efficient method to hide information.
The algorithm SLSB belongs to this type.