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  /  Data Science   /  Can Python Language Help Spies Hide Information in Images?
Python Language

Can Python Language Help Spies Hide Information in Images?

Python language detection techniques help creates advanced image steganography to avoid detection, being efficient for spies.

Image steganography is a technology that hides secret data in all files. Secret data can be in any format, such as text or files. In short, the main motivation for image steganography using Python is to hide the desired information (usually an image, audio, or video) in the Python language without actually changing the appearance of the file. That is, it should look the same as before. We will be focussing on how image steganography using Python can hide secret data in an image, proving quite noteworthy to spies. 

But before diving a little deeper into it, let’s look at what an image comprises.

  • Pixels are the building blocks of an image.
  • Every pixel contains three values: (red, green, and blue) also known as RGB values.
  • Every RGB value ranges from 0 to 255.

This much information is enough to get started.

Now, let’s look at how spies can encode and decode data into the images.

 

Encoding

There are a lot of algorithms that can be used to encode data into the image, and in fact, you can also make one yourself using Python language. 

 

The algorithm is as follows:

For each character in the Python language, its ASCII value is taken and converted into an 8-bit binary. Three pixels are read at a time having a total of 3*3=9 RGB values. The first eight RGB values are used to store one character that is converted into an 8-bit binary. The corresponding RGB value and binary data are compared. If the binary digit is 1 then the RGB value is converted to odd and, otherwise, even. The ninth value determines if more pixels should be read or not. If there is more data to be read, i.e. encoded or decoded, then the ninth-pixel changes to even. Otherwise, if we want to stop reading pixels further, then make it odd. Repeat this process until all the data is encoded into the image.

 

Decoding

For decoding, again, three pixels are read at a time. The first 8 RGB values give us information about the secret data, and the ninth value tells us whether to move forward or not. For the first eight values, if the value is odd, then the binary bit is 1, otherwise, it is 0. The bits are concatenated to a string, and with every three pixels, we get a byte of secret data, which means one character. Now, if the ninth value is even then we keep reading pixels three at a time, or otherwise, we stop.

 

Limitations

This program sometimes might not work as expected with JPEG images because JPEG uses lossy compression which means that the pixels are modified to compress the image and reduce the quality, therefore data loss happens.