1. Steganography in WebP image using LSB embedding
Master’s project defense By
Manchu Viswam

2. Introduction
Steganography is the art of hiding information in ways that prevent the detection of hidden messages.
Steganography means “covered writing.”
The goal of digital steganography are security and capacity.
The basic terms used in steganography are carrier file, message and stego file.
Steganography can be classified into three types, based on the carrier file used. Carrier file can be text, image, audio or video file [2].
Least Significant Bit (LSB) insertion technique is exploited to embed data into a variety of digital media.
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3. LSB insertion
It is a popular and simple approach to embed data in the carrier file.
It replaces least significant bits of the carrier file with the data to be embedded so that it is difficult to be detected by the human eye.
The insertion can be done at any of the bits on the carrier file and it is mostly done in least significant bits to minimize the image distortion.
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4. LSB insertion - Example
When using a 24- bit image, one can change 3 bits in a pixel by changing a RGB color components.
For an example consider, three adjacent pixels of an image and embed binary value of 400 ( ) in the LSB of the carrier file.
After embedding,
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5. Image steganography
In this project, we will use WebP image as the carrier file.
WebP is a new image format by Google, and uses small file size and gives better quality images on the web.
It supports both lossless and lossy compression techniques.
It also supports transparency for both image compressions.
WebP image is divided into sub-blocks. Each sub-block has 4x4 pixels.
It is based on block prediction, the same methodology used by the VP8 video format and it uses the Resource Interchange File Format (RIFF) as a container format.
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6. WebP encoding overview
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7. WebP block decoding
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8. Previous work
LSB steganography has been implemented for lossless image formats such as BMP, GIF, and PNG[Reddy, Reddy, Subramanyam 2011].
LSB steganography has also been implemented for lossy image format like JPEG[Elgabar 2013].
These image formats uses DIIT (Digital Invisible Ink Toolkit) open source Java based tool as the framework for steganography and steganalysis [Hempstalk 2006].
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9. Motivation WebP is a new image format.
It provides lossless and lossy compression for digital images.
In WebP, lossless images are 26% smaller in size when compared to PNG images [7].
In WebP, lossy images are 25-34% smaller in size when compared to JPEG images [7].
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10. Design of LSB algorithm for WebP lossless image steganography
Step1. Select the carrier image (c) as an input. Step2. Encode the c in binary [18]. Step3. The secret message (m). Step4. Encode the m in binary [18]. Step5. Choose one pixel of the c sequentially. Step6. Use that pixel to embed message in the least significant bits. Step7. Repeat step 6 until you embed message completely. Step8. Save the new image called stego image (s). Step9. During steganalysis [4] the stego image is decoded to obtain the hidden message (m).
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11. Design for WebP lossless image steganography
Carrier image (c)
Stego image (s)
Encode c in binary
Message (m)
Encode m in binary
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12. Design for WebP lossless image steganalysis
Stego image (s)
Hidden message (m)
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13. Design of LSB algorithm for WebP lossy image steganography
Step1. Select the carrier image (c) as an input. Step2. WebP image is divided into sub-blocks (4x4), whose values are predicted using the values in neighboring block, so that only the difference is encoded using DCT transform [16]. DCT transform converts each sub-block of an image from the spatial domain into the frequency domain. Step3. Then do quantization to reduce information into a smaller one (coefficients). Step4. The secret message (m). Step5. Encode the m in binary [18]. Step6. Choose one coefficient sequentially. Step7. Use that coefficient to embed message in the least significant bit. Step8. Repeat step 7 until you embed message completely. Step9. After embedding the required message, the modified coefficients are compressed using entropy encoding to produce the stego image. Step10. Save the new image called stego image (s).
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14. Design of LSB algorithm for WebP lossy image steganalysis
Step1: Select the stego image (s) as an input. Step 2: Do the reverse of entropy encoding to get the coefficients. Step 3: From the coefficients we will obtain the hidden message (m).
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15. Design for WebP lossy image steganography [5]
Carrier image (c) 4x4 blocks
Coefficients
DCT
Quantization
Message (m)
Table
Entropy encoding
Stego image (s)
Encode (m) in binary
Table
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16. Design for WebP lossy image steganalysis [5]
Hidden Message (m)
Stego image (s)
Coefficients
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17. Implementation Java development kit jdk 1.7 for 32 bit platform.
Java 32-bit process (Program Files (x86)).
Two prebuilt libraries are utilized -webp-imageio.jar and webp-imageio.dll.
Windows 7 operating system.
Digital Invisible Ink Toolkit 1.6
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18. Evaluation of WebP image steganography - 1
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19. Evaluation of WebP image steganography - 2
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20. Evaluation of WebP image steganography -3
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21. Evaluation of WebP image steganography -4
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22. Evaluation of WebP image steganography - 5
Image Name (.webp)
Mean Squared Error
Normalised Cross-Correlation
UNESCO World Heritage Image
87.455
Kayaker Image
Parkrun Image
Wild Cherry Image
Jaipur Maharaja Brass Band Image
70.211
The mean-squared error (MSE) [4] between carrier image and stego image is:
MSE = (1 / XY) * sum ((p(x, y) - p~(x, y))^2)
The Normalized Cross-Correlation (NC) [4] between carrier image and stego image is:
NC = sum(p(x,y)*p~(x,y)) / sum(p(x,y)^2)
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23. Evaluation of WebP image steganography - 6
Image Format
Payload Capacity
Stealth Ability
WebP
Low
High
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24. Time taken to embed message - comparison
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25. Time taken to retrieve message - comparison
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26. Quantitative and qualitative metrics of WebP with PNG and JPEG
Image Name
Mean Squared Error
Normalised Cross-Correlation
Kayaker. png
0.003
Kayaker. jpg
Kayaker. webp
Image Format
Payload Capacity
Stealth Ability
PNG
High
Low
JPEG
Medium
WebP
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27. Conclusion
We have designed and implemented software to perform WebP steganography.
The DIIT tool is a stand-alone application and can be used on all platforms.
There are two benefits of this WebP steganography.
WebP steganography has higher stealth ability when compared to PNGs and JPEG images.
WebP steganography process takes more time to embed and retrieve messages than the PNGs and the JPEG images. This will improve when Java gets the ability to decode and encode WebP images.
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28. Future work
Implement and experiment the results for WebP lossless steganography. This will involve in creating a new java imageio library to decode and encode WebP lossless images.
Experiment with other steganography techniques in WebP images.
Experiment the results with other message options such as image, audio or video.
Combine cryptography with steganography for additional security.
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29. References
[1] Johnson, Neil F., and Sushil Jajodia. "Exploring steganography: Seeing the unseen." Computer 31, no. 2 (1998):
[2] Abbas Cheddad, Joan Condell, Kevin Curran, Paul Mc Kevitt. “Digital image steganography: Survey and analysis of current methods.” Signal Processing, Volume 90, Issue 3, Pages ,March 2010.
[3] Elgabar, Eltyeb E. Abed, and Haysam A. Ali Alamin. "Comparison of LSB Steganography in GIF and BMP Images." International Journal of Soft Computing and Engineering (IJSCE) ISSN: , Volume-3, Issue-4, September 2013.
[4] Kathryn Hempstalk"Hiding Behind Corners:Using Edges in Images for Better Steganography",January 2006.
[5] Elgabar, Eltyeb E. Abed. "Comparison of LSB Steganography in BMP and JPEG Images." International Journal of Soft Computing and Engineering (IJSCE) ISSN: , Volume-3, Issue-5, November 2013.
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30. References(Continued)
[6] Reddy, V. Lokeswara, A. Subramanyam, and P. Chenna Reddy. "Implementation of LSB steganography and its evaluation for various file formats." Int. J. Advanced Networking and Applications 2, no. 05 (2011):
[7] WebP – Google Developers
[8]Ebrahimi, P. T. wg1n5578 WebP vs. Standard Image Coding. Technical report, ISO/ITU JPEG commitee, ICT-Link, 2010.
[9] Marie Babel “From image coding and representation to robotic vision.” tel , version Nov ouvertes.fr/docs/00/75/45/50/PDF/HDRBabel2012Final_ReducedQuality.pdf
[10] Provos, Niels, and Peter Honeyman. "Hide and seek: An introduction to steganography." Security & Privacy, IEEE 1.3 (2003):
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31. References(Continued)
[11] Chandramouli, Rajarathnam, and Nasir D. Memon. "Steganography capacity: A steganalysis perspective." Electronic Imaging International Society for Optics and Photonics, 2003.
[12] Bankoski, James, Paul Wilkins, and Yaowu Xu. "Vp8 data format and decoding guide." (2011).
[13] Rabbat, Richard ( ). "WebP, a new image format for the Web". Chromium Blog. Google. Retrieved
[14] Jyrki Alakuijala, August 30, 2012.
[15] Morkel, Tayana, Jan HP Eloff, and Martin S. Olivier. "An overview of image steganography." ISSA
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32. References(Continued)
[16] Ginesu, Giaime, Maurizio Pintus, and Daniele D. Giusto. "Objective assessment of the WebP image coding algorithm." Signal Processing: Image Communication 27.8 (2012):
[17] Bennett, Neil R. JPEG STEGANALYSIS & TCP/IP STEGANOGRAPHY. Diss. University of Rhode Island, 2009.
[18] Al-Shatnawi, Atallah M. "A new method in image steganography with improved image quality." Applied Mathematical Sciences 6.79 (2012):
[19] Wu, H-C., et al. "Image steganographic scheme based on pixel-value differencing and LSB replacement methods." IEE Proceedings-Vision, Image and Signal Processing 152.5 (2005):
[20] Wiggins, Richard H., et al. "Image File Formats: Past, Present, and Future 1."Radiographics 21.3 (2001):
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33. References(Continued)
[21] Ahmed, Nasir, T. Natarajan, and Kamisetty R. Rao. "Discrete cosine transform."Computers, IEEE Transactions on (1974):
[22] Ahmed, Nasir, and Kamisetty Ramamohan Rao. "Walsh-hadamard transform."Orthogonal Transforms for Digital Signal Processing. Springer Berlin Heidelberg,
[23] Bankoski, Jim, Paul Wilkins, and Yaowu Xu. "Technical overview of VP8, an open source video codec for the web." ICME
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34. Thank you Questions?
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