Optimizing Distortion in Steganography Using S-T Codesijarcsse.com/Before_August_2017/docs/papers/Volume... · Optimizing Distortion in Steganography Using S-T Codes ... SOFTWARE

© 2013, IJARCSSE All Rights Reserved Page | 176

Volume 3, Issue 6, June 2013 ISSN: 2277 128X

International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com

Optimizing Distortion in Steganography Using S-T Codes ARUN KUMAR.R

1 1assistant Professor,Cse,

Vidya Jyothi Institute Of Technology,

Hyderabad , India

Abstract This paper proposes a complete practical methodology for minimizing additive distortion in steganography with

general (non binary) embedding operation. Let every possible value of every stego element be assigned a scalar expressing

the distortion of an embedding change done by replacing the cover element by this value. The total distortion is assumed

to be a sum of per-element distortions. Both the payload-limited sender (minimizing the total distortion while embedding a

fixed payload) and the distortion-limited sender (maximizing the payload while introducing a fixed total distortion) are

considered. Without any loss of performance, the nonbinary case is decomposed into several binary cases by replacing

individual bits in cover elements. The binary case is approached using a novel syndrome-coding scheme based on dual

convolutional codes equipped with the Viterbi algorithm. This fast and very versatile solution achieves state-of-the-art

results in steganographic applications while having linear time and space complexity w.r.t. the number of cover elements.

We report extensive experimental results for a large set of relative payloads and for different distortion profiles, including

the wet paper channel. Practical merit of this approach is validated by constructing and testing adaptive embedding

schemes for digital images in raster and transform domains. Most current coding schemes used in steganography (matrix

embedding, wet paper codes, etc.) and many new ones can be implemented using this framework.

Keywords: STEGANOGRAPHY, STEGO, MATRIX EMBEDDING, WET PAPER CODES,JAVA, MATLAB, VITERBI

ALGORITHM.

1. INTRODUCTION There exist two mainstream approaches to steganography in empirical covers, such as digital media objects:

steganography designed to preserve a chosen cover model and steganography minimizing a heuristically-defined embedding

distortion. The strong argument for the former strategy is that provable undetectability can be achieved w.r.t. a specificmodel.

The disadvantage is that an adversary can usually rather easily identify statistical quantities that go beyond the chosen model

that allow reliable detection of embedding changes. The latter strategy is more pragmatic—it abandons modeling the cover

source and instead tells the steganographer to embed payload while minimizing a distortion function. In doing so, it gives up

any ambitions for perfect security. Although this may seem as a costly sacrifice, it is not, as empirical covers have been

argued to be incognizable [1], which prevents model-preserving approaches from being perfectly secure as well. While we

admit that the relationship between distortion and steganographic security is far from clear, embedding while minimizing a

distortion function is an easier problem than embedding with a steganographic constraint (preserving the distribution of

covers). It is also more flexible, allowing the results obtained from experiments with blind steganalyzers to drive the design of the distortion function.

In fact, today’s least detectable steganographic schemes for digital images [2]–[5] were designed using this

principle. Moreover, when the distortion is defined as a norm between feature vectors extracted from cover and stego objects,

minimizing distortion becomes tightly connected with model preservation insofar the features can be considered as a low-

dimensional model of covers. This line of reasoning already appeared in [5] and [6] and was further developed in [7]. With

the exception of [7], steganographers work with additive distortion functions obtained as a sum of single-letter distortions. A

well-known example is matrix embedding where the sender minimizes the total number of embedding changes. Near-optimal

coding schemes for this problem appeared in [8] and [9], together with other clever constructions and extensions [10]–[15].

When the single-letter distortions vary across the cover elements, reflecting thus different costs of individual embedding

changes, current coding methods are highly suboptimal [2], [4]. This paper provides a general methodology for embedding

while minimizing an arbitrary additive distortion function with a performance near the theoretical bound. We present a complete methodology for solving both the payload-limited and the distortion-limited sender. The implementation described

in this paper uses standard signal processing tools—convolutional codes with a trellis quantizer—and adapts them to our

problem by working with their dual representation.

These codes, which we call the syndrome-trellis codes (STCs), can directly improve the security of many existing

steganographic schemes, allowing them to communicate larger payloads at the same embedding distortion or to decrease the

http://www.ijarcsse.com/

Arun et al., International Journal of Advanced Research in Computer Science and Software Engineering 3(6),

June - 2013, pp. 176-184


distortion for a given payload. In addition, this work allows an iterative design of to the distortion function to minimize

detectability measured using blind steganalyzers on real cover sources [4], [5], [16]. This paper is organized as follows. In the

next section, we introduce the central notion of a distortion function. The problem of embedding while minimizing distortion

is formulated in Section III, where we introduce theoretical performance bounds as well as quantities for evaluating the performance of practical algorithms with respect to each other and the bounds. The syndrome coding method for

steganographic communication is reviewed in Section IV. By pointing out the limitations of previous approaches, we

motivate our contribution, which starts in Section V, where we introduce a class of syndrome-trellis codes for binary

embedding operations.

We describe the construction and optimization of the codes and provide extensive experimental results on different

distortion profiles including the wet paper channel. In Section VI, we show how to decomposethe problem of embedding

using nonbinary embedding operations to a series of binary problems using a multilayered approach so that practical

algorithms can be realized using binary STCs. The application and merit of the proposed coding construction is demonstrated

experimentally in Section VII on covers formed by digital images in raster and transform (JPEG) domains. Both the binary

and nonbinary versions of payloadand distortion-limited senders are tested by blind steganalysis. Finally, the paper is

concluded in Section VIII. This paper is a journal version of [17] and [18], where the STCs and the multilayered construction

were introduced. This paper unifies these methods into a complete and self-contained framework. Novel performance results and comparisons are included.

2) EXISTING SYSTEM:

In special domain, the hiding process such as least significant bit(LSB) replacement, is done in special domain,

while transform domain methods; hide data in another domain such as wavelet domain.

Least significant bit (LSB) is the simplest form of Steganography. LSB is based on inserting data in the least

significant bit of pixels, which lead to a slight change on the cover image that is not noticeable to human eye. Since this

method can be easily cracked, it is more vulnerable to attacks.

LSB method has intense affects on the statistical information of image like histogram. Attackers could be aware of a

hidden communication by just checking the Histogram of an image. A good solution to eliminate this defect was LSB

matching. LSB-Matching was a great step forward in Steganography methods and many others get ideas from it.

3) PROPOSED SYSTEM:

In this paper it is planned to introduce a method that embed 2 bits information in a pixel and alter one bit from one

bit plane but the message does not necessarily place in the least significant bit of pixel and second less significant bit plane

and fourth less significant bit plane can also host the massage.

Since in our method for embedding two bits message we alter just one bit plane, fewer pixels would be manipulated

during embedding message in an image and it is expected for the steganalysis algorithm to have more difficulty detecting the

covert communication. It is clear that in return complexity of the system would increase.

In our method there are only three ways that a pixel is allowed to be changed:

Its least significant Bit would alter (So the gray level of the pixel would increased or decreased by one

level)

The second less significant bit plane would alter (So the gray level of the pixel would increase or decrease

by two levels)

The fourth less significant bit plane would alter (So the gray level of the pixel would increase or decrease

by eight levels)

4) HARDWARE REQUIREMENTS:

Processor : Any Processor above 500 MHz.

Ram : 128Mb.

Hard Disk : 10 GB.

Compact Disk : 650 Mb.

Input device : Standard Keyboard and Mouse. Output device : VGA and High Resolution Monitor

5 ) SOFTWARE REQUIREMENTS

Operating System : Windows XP.

Coding Language : JAVA

Simulation : MATLAB (for checking Histogram of Original & Stegno image)


June - 2013, pp. 176-184


6) MODULE:

Input Module :

Watermark embedding

Authenticator Watermark

Spread Spectrum

Watermarked content

Modules Description:

1) Input Module :

The Input Module is designed as such a way that the proposed system must be capable of handling any type of data formats,

such as if the user wishes to hide any image format then it must be compatible with all usual image formats such as jpg, gif,

bmp, it must be also compatible with video formats such as avi,flv,wmf etc.. and also it must be compatible with various

document formats, so that the user can be able to user any formats to hide the secret data.

2) Watermark embedding :

Watermarking is a technology for embedding various types of information in digital content. In general, information

for protecting copyrights and proving the validity of data is embedded as a watermark. Watermarked content can prove its origin, thereby protecting the data.

3) Authenticator Watermark :

In this module we encrypt the data embedded image. The purpose of authenticator watermark of a block is invariant in the

watermark embedding process; hence the watermark can be extracted without referring to the original content .The

encryption and decryption techniques used in this module.

4) Spread Spectrum :

We flip an edge pixel in binary images is equivalent to shifting the edge location horizontally one pixel and vertically one

pixel. A horizontal edge exists if there is a transition between two neighboring pixels vertically and a vertical edge exists if

there is a transition between two neighboring pixels horizontally. We use spread spectrum watermark morphological content.

5) Watermarked content

The watermarked content is obtained by computing the inverse for the main processing block to reconstruct its candidate pixels. Use this module we going to see the original and watermarked content.

6) Module I/O:

Module Input:

We give original content as input with watermark data embedding. We view flipping an edge pixel in binary images as

shifting the edge location one pixel horizontally and vertically.

Module Output:

The output of the project is we reconstruct the pixel horizontally and vertically .we can see the original watermarked data and

embedding content.

7) INPUT DESIGN:

The input design is the link between the information system and the user. It comprises the developing specification and

procedures for data preparation and those steps are necessary to put transaction data in to a usable form for processing can be achieved by inspecting the computer to read data from a written or printed document or it can occur by having people keying

the data directly into the system. The design of input focuses on controlling the amount of input required, controlling the

errors, avoiding delay, avoiding extra steps and keeping the process simple. The input is designed in such a way so that it

provides security and ease of use with retaining the privacy. Input Design considered the following things:

What data should be given as input?

How the data should be arranged or coded?

The dialog to guide the operating personnel in providing input.

Methods for preparing input validations and steps to follow when error occur.

7.1 OBJECTIVES:

1.Input Design is the process of converting a user-oriented description of the input into a computer-based system. This design is important to avoid errors in the data input process and show the correct direction to the management for getting correct

information from the computerized system.

2. It is achieved by creating user-friendly screens for the data entry to handle large volume of data. The goal of designing

input is to make data entry easier and to be free from errors. The data entry screen is designed in such a way that all the data

manipulates can be performed. It also provides record viewing facilities.

3.When the data is entered it will check for its validity. Data can be entered with the help of screens. Appropriate messages

are provided as when needed so that the user will not be in maize of instant. Thus the objective of input design is to create an

input layout that is easy to follow


June - 2013, pp. 176-184


8) OUTPUT DESIGN:

A quality output is one, which meets the requirements of the end user and presents the information clearly. In any system

results of processing are communicated to the users and to other system through outputs. In output design it is determined

how the information is to be displaced for immediate need and also the hard copy output. It is the most important and direct source information to the user. Efficient and intelligent output design improves the system’s relationship to help user

decision-making.

1. Designing computer output should proceed in an organized, well thought out manner; the right output must be developed

while ensuring that each output element is designed so that people will find the system can use easily and effectively. When

analysis design computer output, they should Identify the specific output that is needed to meet the requirements.

2.Select methods for presenting information.

3.Create document, report, or other formats that contain information produced by the system.

The output form of an information system should accomplish one or more of the following objectives.

Convey information about past activities, current status or projections of the

Future.

Signal important events, opportunities, problems, or warnings.

Trigger an action. Confirm an action.

9. SYSTEM TESTING

The purpose of testing is to discover errors. Testing is the process of trying to discover every conceivable fault or

weakness in a work product. It provides a way to check the functionality of components, sub assemblies, assemblies and/or a

finished product It is the process of exercising software with the intent of ensuring that the

Software system meets its requirements and user expectations and does not fail in an unacceptable manner. There are various

types of test. Each test type addresses a specific testing requirement.

9.1 TYPES OF TESTS:

9.1.1Unit testing:

Unit testing involves the design of test cases that validate that the internal program logic is functioning properly, and

that program inputs produce valid outputs. All decision branches and internal code flow should be validated. It is the testing of individual software units of the application .it is done after the completion of an individual unit before integration. This is

a structural testing, that relies on knowledge of its construction and is invasive. Unit tests perform basic tests at component

level and test a specific business process, application, and/or system configuration. Unit tests ensure that each unique path of

a business process performs accurately to the documented specifications and contains clearly defined inputs and expected

results.

9.1.2 Integration testing:

Integration tests are designed to test integrated software components to determine if they actually run as one

program. Testing is event driven and is more concerned with the basic outcome of screens or fields. Integration tests

demonstrate that although the components were individually satisfaction, as shown by successfully unit testing, the

combination of components is correct and consistent. Integration testing is specifically aimed at exposing the problems that

arise from the combination of components.

9.1.3 Functional test: Functional tests provide systematic demonstrations that functions tested are available as specified by the business and

technical requirements, system documentation, and user manuals.

Functional testing is centered on the following items:

Valid Input : identified classes of valid input must be accepted.

Invalid Input : identified classes of invalid input must be rejected.

Functions : identified functions must be exercised.

Output : identified classes of application outputs must be exercised.

Systems/Procedures: interfacing systems or procedures must be invoked.

Organization and preparation of functional tests is focused on requirements, key functions, or special test cases. In

addition, systematic coverage pertaining to identify Business process flows; data fields, predefined processes, and successive

processes must be considered for testing. Before functional testing is complete, additional tests are identified and the effective value of current tests is determined.

9.1.4 System Test:

System testing ensures that the entire integrated software system meets requirements. It tests a configuration to ensure

known and predictable results. An example of system testing is the configuration oriented system integration test. System

testing is based on process descriptions and flows, emphasizing pre-driven process links and integration points.

9.1.5 White Box Testing:

White Box Testing is a testing in which in which the software tester has knowledge of the inner workings, structure and

language of the software, or at least its purpose. It is purpose. It is used to test areas that cannot be reached from a black box

level.


June - 2013, pp. 176-184


9.1.6 Black Box Testing:

Black Box Testing is testing the software without any knowledge of the inner workings, structure or language of the

module being tested. Black box tests, as most other kinds of tests, must be written from a definitive source document, such as

specification or requirements document, such as specification or requirements document. It is a testing in which the software under test is treated, as a black box .you cannot ―see‖ into it. The test provides inputs and responds to outputs without

considering how the software works.

10.1 Unit Testing:

Unit testing is usually conducted as part of a combined code and unit test phase of the software lifecycle, although it

is not uncommon for coding and unit testing to be conducted as two distinct phases.

Test strategy and approach

Field testing will be performed manually and functional tests will be written in detail.

Test objectives

All field entries must work properly.

Pages must be activated from the identified link.

The entry screen, messages and responses must not be delayed.

Features to be tested

Verify that the entries are of the correct format

No duplicate entries should be allowed

All links should take the user to the correct page.

10.2 Integration Testing

Software integration testing is the incremental integration testing of two or more integrated software components on

a single platform to produce failures caused by interface defects.

The task of the integration test is to check that components or software applications, e.g. components in a software

system or – one step up – software applications at the company level – interact without error.

Test Results: All the test cases mentioned above passed successfully. No defects encountered.

10.3 Acceptance Testing

User Acceptance Testing is a critical phase of any project and requires significant participation by the end user. It

also ensures that the system meets the functional requirements.

Test Results: All the test cases mentioned above passed.

11. SAMPLE SCREENS:

11.1 Screenshots:


June - 2013, pp. 176-184



June - 2013, pp. 176-184



June - 2013, pp. 176-184


Reference [1] R. Böhme, ―Improved Statistical Steganalysis UsingModels of Heterogeneous Cover Signals,‖ Ph.D. dissertation,

Faculty of Comput. Sci., Technische Universität, Dresden, Germany, 2008.

[2] Y. Kim, Z. Duric, and D. Richards, ―Modified matrix encoding technique for minimal distortion steganography,‖ in

Proc. 8th Int. WorkshopInf. Hiding, J. L. Camenisch, C. S. Collberg, N. F. Johnson, andP. Sallee, Eds., Alexandria,

VA, Jul. 10–12, 2006, vol. 4437, Lecture Notes in Computer Science, pp. 314–327.

[3] R. Zhang, V. Sachnev, and H. J. Kim, ―Fast BCH syndrome coding for steganography,‖ in Proc. 11th Int. Workshop

Inf. Hiding,, S. Katzenbeisserand A.-R. Sadeghi, Eds., Darmstadt, Germany, Jun. 7–10, 2009, vol. 5806, Lecture

Notes in Computer Science, pp. 31–47.

[4] V. Sachnev, H. J. Kim, and R. Zhang, ―Less detectable JPEG steganography method based on heuristic optimization

and BCH syndrome coding,‖ in Proc. 11th ACM Multimedia Security Workshop, J. Dittmann, S. Craver, and J. Fridrich, Eds., Princeton, NJ, Sep. 7–8, 2009, pp. 131–140.

[5] T. Pevný, T. Filler, and P. Bas, ―Using high-dimensional image models to perform highly undetectable

steganography,‖ in Proc. 12th Int. Workshop Inf. Hiding, P. W. L. Fong, R. Böhme, and R. Safavi-Naini, Eds.,

Calgary, Canada, Jun. 28–30, 2010, vol. 6387, Lecture Notes in Computer Science, pp. 161–177.

[6] J. Kodovský and J. Fridrich, ―On completeness of feature spaces in blind steganalysis,‖ in Proc. 10th

ACMMultimedia SecurityWorkshop, A. D. Ker, J. Dittmann, and J. Fridrich, Eds., Oxford, U.K., Sep. 22–23, 2008,

pp. 123–132.

[7] T. Filler and J. Fridrich, ―Gibbs construction in steganography,‖ IEEETrans. Inf. Forensics Security, vol. 5, pp. 705–

720, Sep. 2010.

[8] J. Fridrich and T. Filler, ―Practical methods for minimizing embeddingimpact in steganography,‖ in Proc. SPIE,

Electron. Imag., Security, Steganography, Watermark. Multimedia Contents IX, E. J. Delp and P. W. Wong, Eds., San Jose, CA, Jan. 29–Feb. 1, 2007, vol. 6505, pp. 02–03.

[9] T. Filler and J. Fridrich, ―Binary quantization using belief propagation over factor graphs of LDGM codes,‖

presented at the 45th Annu. Allerton Conf. Commun., Control, Comput., Allerton, IL, Sep. 26–28, 2007.

[10] X. Zhang, W. Zhang, and S. Wang, ―Efficient double-layered steganographic embedding,‖ Electron. Lett., vol. 43,

pp. 482–483, Apr. 2007.

[11] W. Zhang, S. Wang, and X. Zhang, ―Improving embedding efficiency of covering codes for applications in

steganography,‖ IEEE Commun. Lett., vol. 11, pp. 680–682, Aug. 2007.

[12] W. Zhang, X. Zhang, and S. Wang, ―Maximizing steganographic embedding efficiency by combining Hamming

codes and wet paper codes,‖ in Proc. 10th Int. Workshop Inf. Hiding, , K. Solanki, K. Sullivan, and U. Madhow, Eds.,

Santa Barbara, CA, Jun. 19–21, 2008, vol. 5284, Lecture Notes in Computer Science, pp. 60–71.

[13] T. Filler and J. Fridrich, ―Wet ZZW construction for steganography,‖ presented at the 1st IEEE Int. Workshop Inf.

Forensics Security, London, U.K., Dec. 6–9, 2009. [14] W. Zhang and X. Zhu, ―Improving the embedding efficiency of wetpaper codes by paper folding,‖ IEEE Signal

Process. Lett., vol. 16, pp.794–797, Sep. 2009.

[15] W. Zhang and X. Wang, ―Generalization of the ZZW embedding construction for steganography,‖ IEEE Trans. Inf.

Forensics Security, vol. 4, pp. 564–569, Sep. 2009.

[16] J. Fridrich, T. Pevný, and J. Kodovský, ―Statistically undetectable JPEG steganography: Dead ends, challenges, and

opportunities,‖ in Proc. 9th ACM Multimedia Security Workshop, J. Dittmann and J. Fridrich, Eds., Dallas, TX, Sep.

20–21, 2007, pp. 3–14.


June - 2013, pp. 176-184


[17] T. Filler, J. Judas, and J. Fridrich, ―Minimizing embedding impact in steganography using trellis-coded quantization,‖

in Proc. SPIE, Electron. Imag., Security, Forensics Multimedia XII, N. D. Memon, E. J.Delp, P. W. Wong, and J.

Dittmann, Eds., San Jose, CA, Jan. 17–21,2010, vol. 7541, pp. 05-01–05-14.

[18] T. Filler and J. Fridrich, ―Using non-binary embedding operation to minimize additive distortion functions in steganography,‖ presented at the 2nd IEEE Int.Workshop Inf. Forensics Security, Seattle,WA, Dec. 12–15, 2010.

[19] S. I. Gel’fand and M. S. Pinsker, ―Coding for channel with randomparameters,‖ Problems Control Inf. Theory, vol. 9,

no. 1, pp. 19–31,1980.

[20] A. D. Ker, ―Batch steganography and pooled steganalysis,‖ in Proc.8th Int. Workshop Inf. Hiding, J. L. Camenisch,

C. S. Collberg, N. F.Johnson, and P. Sallee, Eds., Alexandria, VA, Jul. 10–12, 2006, vol.4437, Lecture Notes in

Computer Science, pp. 265–281.

[21] C. E. Shannon, ―Coding theorems for a discrete source with a fidelitycriterion,‖ IRE Nat. Conv. Rec., vol. 4, pp. 142–

163, 1959.

Authors Biography

ARUN KUMAR.R Completed M.TECH in CSE with specialization (COMPUTER SCIENCE

ENGINEERING) from CVSR college of engineering affiliated by JNTUH in 2012. Currently he is

working as an Assistant professor in CSE department at Vidya Jyothi Institute of Technology, Hyderabad.

he is having 4 years experience as an assistant professor.he published 3 international journals. His areas of

research interests include NETWORKS, ANALYSIS OF ALGORITHM, COMPILER AND

LANGUAGE PROCESSING.

Documents

Optimizing Distortion in Steganography Using S-T Codesijarcsse.com/Before_August_2017/docs/papers/Volume... · Optimizing Distortion in Steganography Using S-T Codes ... SOFTWARE