Project presentation on Image Steganography using MATLAB. Project under Digital Design, Signals and Systems and Communication System.
Tool Used - MATLAB
2. What is Steganography ?
Steganography is the science of writing hidden messages in such a way that no one apart from sender and intended recipient
even realizes there is a hidden message. There are often cases when it is not possible to send messages openly or in encrypted
form.This is where steganography can come into play. While cryptography provides privacy, steganography is intended to
provide secrecy.The aim of steganography is to hide the secret messages and also for communication and transferring of data.
So no one apart from the authorized sender and receiver will be aware of the existence of the secret data
In modern approach, depending on the cover medium, steganography can be divided into four types that are Text Steganography
,Image Steganography ,Audio Steganography ,Video Steganography
Figure 1.1 The same image revealed different hidden numbers when viewed through white, blue, green, and red lights.
3. An image is nothing more than a two dimensional signal. It is defined by the mathematical
function f(x,y) where x and y are the two co-ordinates horizontal and vertical.
The value of f(x,y) at any point is gives the pixel value at that point of an image.
What is an Image ?
Each number represents the value of the function f(x,y) at any point. In this case the
value 128 , 230 ,123 each represents an individual pixel value.
The dimensions of the picture is actually the dimensions of this two dimensional array.
I will be performing Image steganography so lets discuss what an image is
128
232
80 255
123
230 123
321
255
Figure 1.2 Original Image
4. The Least Significant Bit (LSB) technique modifies and replaces the last bit of each pixel with the secret message's data bit.
Basic Principle
A digital image is made up of a finite number of digital values called pixels. Pixels are the tiniest individual elements in an image,
storing values that represent a given color's brightness at any given time.
As a result, an image can be thought of as a pixel matrix (or two-dimensional array) with a predetermined number of rows and
columns.
As can be seen , changing the MSB has a larger impact on the final value than changing the LSB, so we use least significant bit
steganography.
1
0 1
1
1 1
1
1
MSB LSB
Value - 255
Value - 127
Huge Change in bytes Minimal Change in bytes
Value - 254
1
1
1 1
1
1 1
1
1 1
1
1 1
1
1 0
Figure 1.3 Cover Image
5. [(225),(155),(99),(15),(155),(63),(1),(99),(219),(69),(18),(25)]
[(224),(154),(99),(14),(154),(63),(1),(99,(219),(69),(18),(25)]
How LSB technique works ?
Each pixel has an associated value that represents grey scale values ranging from 0 to 255, or 8-bit values.
Let's look at an example of how this technique works. Let's say we want to conceal the message "hi" in a 44 image with the
following pixel values:
Using the ASCII Table, we can convert the secret message into decimal
values and then into binary: 01101000110101. Now we convert each pixel
value to binary and replace each least significant bit with the message bits
in order (for example, 225 is 11100001, and we replace the last bit with the
first data bit(0), and so on). The pixel values will only change by +1 or -1,
which will be barely noticeable.
here is the changed pixel values they will have a minimal effect on image
Cover Image
Cover Image
Text
Stego Image
Text
Encryption Algorithm
Encryption Algorithm
Figure 1.4 Working of LSB
6. The following is the methodology used by the programme:
Algorithm for LSB
Cover Image: The image which is to be used to hide the data.
Stego Image: The image which has been embedded with the hidden data.
Convert the secret message to binary format.
Convert the image on the cover to grayscale. (Using grayscale is more convenient because an 8-bit per pixel grayscale image
has 8 bit sequences versus a 24-bit per pixel colored image with 24-bit sequences.)
Take the intensity value (which ranges from 0 to 255) for each pixel in the image and convert it to binary format.
Replace the right-most bit, also known as the LSB, with a bit from the secret message.
Repeat until all of the secret message's bits have been embedded. After that, the image will be referred to as a stego image.
7. Implementation
After running the first set of the code the original image would be displayed
After excecuting the second part the user will have to input the message which is to be hidden in the image. Here the message
"Matrix Laboratory" is used as an example for message that needs to be hidden.
Figure 1.7 Original Image
8. Implementation
After the message input by the used the program will return the grey scaled image that is cover image and stego image which
stores the hidden message at the output
Finally, the decoding programme will be run to uncover the stego image's hidden message using the same technique through
which the image is encoded
Figure 1.8 Cover & Stego Images
9. This method is very fast and easy to implementin comparison to other methods of steganography
The output image has very slightly difference to the input image
Instead of embedding the message in only the LSB we can embed the message in last two LSBs thus embedding even large
messages
This method forms the basics of many other complex algorithms
Instead of embedding the messages in only the LSB, we can embed the messages in last two LSBs,thus embedding even large
messages
This type of encodin the data is weak since it can be easily decoded by taking the LSB of the image and getting the message
in binary fomat
This method is too old because it was used long ago when other encodin methods were not yet developed.
When embedding the message in more than one LSB, the image quality may reduce depending on how many pixels are
changed.
Advantages
Disadvantages
Advantages & Disadvantags
10. Image steganography is used in Cyber Forensics
It is also used by Intelligence services
Copyright and to avoid piracy of intellectual rights
Secure Highly confidential files and data
Protect original data from unknown sources.
Applications
11. Mujtiba, Syed & Yousu, Salihah & Bisma, Syed & Siddiqi, Mehvish & Khaki, Zahidgulzar. (2017). COMPARISION OF LSB AND
DWT STEGANOGRAPHY TECHNIQUES. 10.21090/IJAERD.ETIECE08.
Macit, Hüseyin & Koyun, Arif & Güngör, Orhan. (2018). A REVIEW AND COMPARISON OF STEGANOGRAPHY TECHNIQUES.
Fahim Irfan et. Al. ‘s (2011) “An Investigation into Encrypted Message Hiding through Images Using LSB ”, International
Journal of EST,
Rajkumar Yadav, (2011) “A Novel Approach For Image Steganography In Spatial Domain Using Last Two Bits of Pixel Values”,
International Journal of Security, Vol.5 Iss. 2 pp. 51-61.
References
