NEW CHANNEL SELECTION RULE FOR JPEG STEGANOGRAPHY

OBJECTIVE:

To improve higher security performance and reducing errors, the main

role of this project as present a new channel selection rule for Joint

Photographic Experts Group Steganography.

PROBLEM DIFINITION:

The composite signal is subject to video lossy compression to become.

The message should survive the video lossy compression and can be identically

extracted from. This robustness constrain should have low distortion effect on

the reconstructed video as well as low effect on the data size (bit rate). Given

that can be identically extracted, in this paper; we use two metrics to evaluate

data-hiding algorithms in compressed video which are:

1. Increase in data size: representing the overhead price paid for the

embedded data;

2. Drop in the reconstruction quality: this reconstruction is with

quality loss than that without data hiding and is denoted by and

expressed as the PSNR difference which is as well that of the

quantity of the relative error and for P- and B-frame, respectively.

ABSTRACT:

This paper deals with data hiding in compressed video. Unlike data

hiding in images and raw video which operates on the images themselves in the

spatial or transformed domain which are vulnerable to steganalysis, we target

the motion vectors used to encode and reconstruct both the forward predictive

(P)-frame and bidirectional (B)-frames in compressed video. The choice of

candidate subset of these motion vectors are based on their associated macro

block prediction error, which is different from the approaches based on the

motion vector attributes such as the magnitude and phase angle.

A greedy adaptive threshold is searched for every frame to achieve

robustness while maintaining a low prediction error level. The secret message

bit stream is embedded in the least significant bit of both components of the

candidate motion vectors. The method is implemented and tested for hiding data

in natural sequences of multiple groups of pictures and the results are evaluated.

The evaluation is based on two criteria: minimum distortion to the reconstructed

video and minimum overhead on the compressed video size. Based on the

aforementioned criteria, the proposed method is found to performwell and is

compared to a motion vector attribute-based method from the literature.

EXISTING SYSTEM:

The Existing System contained only steganography process for data

transfer without any security prediction. In this system developed new channel

selection method for data hiding, but it didn’t use any advanced methods and

factors for data hiding. So that, It produce lot of errors in the timing for image

decompress.

DISADVANTAGES:

Less Security

High amount of Perturbation Errors

Very difficult for Image Decompression

PROPOSED SYSTEM:

In proposed system contain advanced Perturbed Quantization rule for

data hiding. The process of data hiding as follows,

LSB Algorithm

Embedding data, which is to be hidden, into an image requires two files.

The first is an innocent looking image that will hold the hidden

information, called the cover image.

The second file is the message – the information to be hidden

ADVANTAGES:

Minimal detectable distortion

Higher security performance

ALGORITHM USED:

1. LSB (Least Significant Bit)

2. AES (Advanced Encryption Standard)

ARCHITECTURE DIAGRAM:

SYSTEM REQUIREMENTS:

Hardware requirements:

Intel Pentium IV

256/512 MB RAM

1 GB Free disk space or greater

1 GB on Boot Drive

17” XVGA display monitor

1 Network Interface Card (NIC

Input Image

File

Output

Image File

Discrete Cosine

Transform

Dividing And

Rounding Matrix

Entropy Encoder

Compressed

Image File

Encode Secret

Image Bits

Software requirements:

MS Windows XP/2000

MS IE Browser 6.0/later

MS .Net Framework 4.0

MS Visual Studio.Net 2005

Internet Information Server (IIS)

MS SQL Server 2005

Windows Installer 3.1

APPLICATIONS:

1. Deductive Agencies

2. Government Secret Code

3. Military Agencies