A Project On

“BLIND RECOVERY OF COVERED DATA FROM DIGITAL CARRIER ”

Presented By-NIKAM AJINKYAHARBA VIJAYAVHAD SOMINATH

GUIDED BY-

Prof. M.N KALE

Introduction Existing System Proposed System Encryption Techniques Decryption Technique Results Advantages Conclusion Reference

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Outline

Digital Data embedding.

Applications may vary.

Improved Embedding performance.

Improved recovery performance.

Extension to limited attacking.

After extracting the data hidden original image is retrieved.

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Introduction What Is Data Hiding ?

Reversible Data Hiding technique image is compressed and encrypted

Secret encryption key used can access the image and decrypt

After extracting the data hidden original image is retrieved.

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EXISTING SYSTEM

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Compressed and Encrypted use in Existing System

Reduce the risk of using Cryptography algorithm alone.

Cryptography algorithm + Information hiding technique.

Symmetric key Encryption.

Attention on the blind recovery of secret data hidden.

Encryption algorithm remain hidden from host.

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PROPOSED SYSTEM

Vessel data.

Steganography is that embedding capacity is very large.

For a 'normal' image, roughly 50% of the data might be replaceable with secret data.

Password use as a symmetric key.

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Steganography

Image Encryption.

Size of image The host image is an 8-bit or higher grey level image

For color host images, the binary cipher text can be inserted into one or all of the RGB components.

Image encryption:

Image Decryption.

For color images, the data is decomposed into each RGB component

Each 1-bit layer is extracted and correlated with the appropriate cipher.

into an 8-bit image based on floating point numbers.

Image decryption

SYSTEM ARCHITECTURE

Random Distribution of Message

Generation of Seed

Random position Selection

Bit Smarter

1-Hide And Seek

Input : Message,shared secret,cover image,seed.Output : Stego image.initialize with shared seedwhile data left to embed do

get pixel from cover imageif pixel !=0 and pixel !=1 thenget next LSB from messagereplace LSB with Message LSBend ifinsert pixel into stego image

end while

Hide And Seek Algorithm

Color Base

• There is a large amount of redundant bits in an image. The redundant bits of an object are those bits that can be altered.

• The alteration cannot be visibly detected by human eyes, due to use of blue color.

• Every pixel in a color image composed of three colors Red, Green and Blue so every pixel contains 24 bits

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LSB• Replaces the least significant bit of cover image

with the message bits.. • Image alteration is not perceptible for any human

eyes as its value will affect the pixel value only by “1”. • So, this property is used to hide the data in the

image. Here we have considered last two bits as LSB bits as they will affect the pixel value only by “3”.

Divide the cover image into set of groups (2x 8)pixel.

Separate the R, G and B band of each pixel. Extract hash value. Random number generation Use hash values to determine the selected

pixel for each block. Data bits are replaced on selected pixels

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2-LFSR(Linear feedback shift register)

M-IGLS

1. First Convert Host Image To Observation Vector Form y(m), m=1,2…...m 2. Create Partition N1.N2/M

3. Number Of Carrier Used By Embedder.

4. Finding Noisy region.

5. Create M-IGLS Header

6. Stego Analysis.

• H - Host image• M - finite image alphabet.• N1,N2 – image size in pixel.

Image

Algorithm

Results

Encoding Process

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Images

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Decoding Process

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Decoded Message

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Advantages1) Confidential communication and secret data storing

2) Protection of data alteration

3)Access control system for digital content distribution

4) Media Database systems

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Applications

1)Confidential communication and secret data storing

2)Protection of data alteration

3)Access control system for digital content distribution

4)Use in Military application to Protect data.

5)Use To Protect data In School , Colleges , Office

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Conclusion

For Experimental studies we have taken four different algorithms for encryption Hide And Seek, LFSR, Single Bit LSB, Color Based. and we decrypted the Message from our Single Static Algorithm MIGLS. with Attention on the blind recovery of secret data hidden in medium.

Hence in this project in decryption phase algo decrypt the Message from stego image by using Single Static Algorithm MIGLS successfully.

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Reference

1] Extracting Spread-Spectrum Hidden Data from Digital Media Ming Li, Member,IEEE, Michel Kulhandjian, Dimitris A. Pados, Member, IEEE, Stella N. Batalama, Senior Member, IEEE, and Michael J. Medley, Senior Member IEEE,IEEE Transactions on Secure Computing vol:8 NO:7 2013.

2] Literature Survey On Modern Image Steganographic Techniques Priya ThomasDepartment of Computer Science and Engineering Nehru College of Engineering and Research Center, Kerala, India.International Journal of Engineering Research Technol-ogy Issue 5, May - 2013 ISSN: 2278-0181.

3] M. Li, D. A. Pados, S. N. Batalama, and M. J. Medley, ”Passive spreadspectrumsteganalysis,” in Proc. IEEE Intern. Conf. Image Proc. (ICIP), Brussels, Belgium,Sept. 2011, pp. 1997-2000.

4] A. Valizadeh and Z. J. Wang, ”Correlation-and-bit-aware spread spectrum embedding for data hiding,” IEEE Trans. Inform. Forensics and Security, vol. 6 , pp. 267-282,June 2011.