Adaptive Steganalysis Based on Embedding Probabilities of Pixels using matlab

ABSTRACT

In modern steganography, embedding modifications are highly concentrated on the textural regions within an image, as such regions are difficult to model for steganalysis. 
Previous studies have shown that compared with non-adaptive strategies, this content adaptive strategy achieves stronger security against existing steganalysis.
Based on the experiments and analyses, however, we found that this embedding property would inevitably lead to a large limitation in existing adaptive steganography.
That is, it is possible for steganalyzers to estimate the regions that have probably been modified after data hiding. 
We use fuzzy based improved SPHIT algorithm.

EXISTING SYSTEM

Embedding modifications are highly concentrated on the textural regions within an image.

Regions are difficult to model for steganalysis.

Previous studies have shown that compared with non-adaptive strategies.

This embedding property would inevitably lead to a large limitation in existing adaptive steganography.

It is possible for steganalyzers to estimate the regions that have probably been modified after data hiding.


PROPOSED SYSTEM


We propose an adaptive steganalytic scheme Fuzzy based improved SPIHT algorithm.

We can concentrate our attention on the regions that have probably been modified and significantly reduce the impact of other unchanged smooth regions.

To improve Signal to noise ration and Bits per pixels we approach code book algorithm.

BLOCK DIAGRAM 

SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS

Processor Type                     : Pentium -IV
Speed                                    : 2.4 GHZ
Ram                                      : 128 MB RAM
Hard disk                              : 20 GB HD

SOFTWARE REQUIREMENTS

Operating System                      : Windows 7 
Software Programming Package        : Matlab R2014b