Suitability of lacunarity measure for blind steganalysis

Blind steganalysis performance is influenced by several factors including the features used for classification. This paper investigates the suitability of using lacunarity measure as a potential feature vectorfor blind steganalysis. Differential Box Counting (DBC) based lacunarity measure has been employed using the traditional sequential grid (SG) and a new radial strip (RS) approach. The performance of the multi-class SVM based classifier was unfortunately not what was expected. However, the findings show that both the SG and RS lacunarity produce enough discriminating features that warrant further research

Data Transfer through an Image and Its Recovery Causing Minimum Distortion in the Carrier Image: A Survey

This paper, tries to address the problem of transmitting the huge amount of data over a communication channel hidden into an image and making sure that there is minimum distortion created into the image carrying that secret data. In this project the sender or the data owner who wants to send his data first encrypts the data and then store that encrypted data in such an efficient way that it required minimum number of bits to be altered to hide the data into an Image. This efficiency is created using the LFSR algorithm which is applied on the secret key which in turn creates a unique set of keys which are checked and used for hiding the data. The data too is not hidden sequentially into an image, it is hidden randomly based on the secret key making it more complicated. Once the data is hidden the image the, it is encrypted using the AES algorithm. Here too it adds the encryption in parallel where the image is divided into equal parts and then the AES algorithm is applied to all the parts of the image simultaneously, thus saving our time in the encryption process. Thus shows a significant time saving in case the large images are used. This image when encrypted is send to the receiver and at the receivers end ,the one who has the correct keys can only get back the original image and the secret data. This makes sure that the receiver get the correct data and the image with minimum distortion