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Fast Matrix Embedding by Matrix Extending

Platform : java

IEEE Projects Years : 2012 - 13

Fast Matrix Embedding by Matrix Extending

 

Abstract

 

When designing steganographic schemes, matrix embedding is an efficient method for increasing the embedding efficiency that is defined as an average number of bits embedded via per change on the cover. Random linear code-based matrix embedding can achieve high embedding efficiency but cost much in computation. In this paper, we propose a method to increase the embedding speed of matrix embedding by extending the matrix via some referential columns. Compared with the original matrix embedding, the proposed method can exponentially reduce the computational complexity for equal increment of embedding efficiency. Experimental results also show that this novel method achieves higher embedding efficiency and faster embedding speed than previous fast matrix embedding methods, and thus is more suitable for real-time steganogaphic systems.

 

Existing System

 

Additive Distortion in Steganography uses linear codes, which is also called syndrome coding or coset encoding. It embeds and extracts a message by using the parity check matrix of a linear code. This method the efficiency is low.

 

Proposed System

 

We proposed a fast matrix embedding method for data hiding by appending referential columns to the parity check matrix. The novel method can significantly reduce the computational complexity of the original matrix embedding, and achieve higher embedding efficiency and embedding speed than previous fast matrix embedding methods. By adjusting the parameters and, the user can flexibly make a trade-off between the embedding efficiency and embedding speed. This method can be used to design real-time steganographic system.

 

Hardware Requirements

 

  • SYSTEM             : Pentium IV 2.4 GHz
  • HARD DISK        : 40 GB
  • MONITOR           : 15 VGA colour
  • MOUSE               : Logitech.
  • RAM                    : 256 MB

 

Software Requirements

 

  • Operating system           :- Windows XP Professional
  • Front End             : - Eclipse.
  • Coding Language :- Java Swing

 

 

 

 

 

Modules

 

  1. Network Module.
  2. Matrix embedding Method.

 

 

 

  1. Appending Columns module.

 

 

 

  1. Extraction by Matrix Extending Module.

 

 

 

Module Description

 

 

 

  1. 1.     Network Module

 

Client-server computing or networking is a distributed application architecture that partitions tasks or workloads between service providers (servers) and service requesters, called clients. Often clients and servers operate over a computer network on separate hardware. A server machine is a high-performance host that is running one or more server programs which share its resources with clients. A client also shares any of its resources; Clients therefore initiate communication sessions with servers which await (listen to) incoming requests.

 

  1. 2.     Matrix embedding Method.

 

 

 

The original matrix embedding, when the number of random columns(K) increases, the solution space of  is exponentially expanded, and thus we have more chances to find a solution with smaller Hamming weight. That is why the embedding efficiency can be improved when increases, but the computational complexity of searching for this solution exponentially grows. In this section, we propose a novel method, by which we can also exponentially expand the solution space, but only cost linearly increasing time to search the solution space. The key idea of the proposed method is to append some referential columns to the matrix.

 

 

 

  1. 3.     Appending Columns module.

 

 

 

By appending referential columns, the size of the solution space is expanded from to; therefore, the expectation of Hamming weight of the minimal-weight solution will decrease, which will lead to increasing embedding efficiency. In the original matrix embedding, by adding random columns, i.e., let the code dimension, we can also get a solution space with the same expanded size, and thus expect a similar increment of embedding efficiency,

 

 

 

 

 

 

 

 

 

 

 

 

 

  1. 4.     Extraction by Matrix Extending Module.

 

 

 

This new method as matrix extending because we design the fast algorithm by appending some referential columns to the parity check matrix. Analysis and experimental results show that the proposed method can flexibly trade embedding efficiency for embedding speed, or vice versa. Compared with the original matrix embedding, the proposed method can exponentially decrease computational complexity by increasing the number of the referential columns while achieving an equal increment of embedding efficiency.

 

 



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