Have you ever wondered how secret messages could be concealed within innocent-looking images? The answer lies in a fascinating technique called steganography, where information is hidden within digital media such as images, audio, or video, without arousing suspicion. In this post, we’ll explore how steganography employs the manipulation of the least significant bit (LSB) to hide text within an image.
“In steganography, hiding text in an image involves modifying the least significant bit (LSB) of the pixels in the image. The LSB is the bit in the binary representation of a number that represents the smallest unit of change. By altering the LSB of each pixel in the image, small changes are made that are imperceptible to the human eye but can be detected using special software or algorithms.”
While Copilot/GPT-4 provides a basic explanation, it lacks clarity on some fundamental concepts. Let’s break it down further:
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Binary Representation: Before modifying the LSB, the text message needs to be converted into binary format. Each character in the text is represented by a unique sequence of binary digits (0s and 1s) according to the ASCII or Unicode encoding standards.
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Modifying LSB: Once the text message is converted into binary, the LSB of each pixel in the image is altered to encode the binary representation of the text. This alteration is minimal and does not significantly change the appearance of the image to the human eye.
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Reconstruction: To extract the hidden text from the steganographic image, the LSB of each pixel is examined and reconstructed into binary form. The binary sequence is then converted back into text using the appropriate encoding scheme.
Steganography is a powerful tool for covert communication, utilizing the subtle manipulation of bits within digital media. By understanding how the least significant bit can hide text within an image, we gain insight into the intricate world of information concealment.
Prompt: Create a post about how steganography can be used to hide text in an image by modifying the least significant bit. The title of your post must contain the word “bit” or “bits”. Start by asking Copilot or GPT4 to explain how it’s done. If you are having trouble getting Copilot to work, stop in at the media services desk in the library. If the response contains phrases like “Discrete Cosine Transform (DCT)”, modify your prompt and try again. Include your prompt and the full text returned by Copilot/GPT4 at the end of your post. Critically examine the explanation from Copilot/GPT4: Identify areas where the explanation is weak and improve it. For example, if Copilot says “Convert the text message into binary” without explaining how that works, you’ll need to explain it or ask Copilot to explain it. Each time you use the output from Copilot/GPT4, add the prompt and the text returned at the end of your post. Add illustrations (photos of hand-drawn illustrations are fine) to illustrate the process described in the text. At the end of your post include an estimate of how much of the explanation in your post is from GPT and how much is from you/your class notes. When you are done, paste the URL for your post to the end of this assignment and submit it.
