Understanding-Steganography-With-Python
LSB Image Steganography Using Python
Steganography is the science that involves communicating secret data in an appropriate multimedia carrier, e.g., image, audio, and video files. It comes under the assumption that if the feature is visible, the point of attack is evident, thus the goal here is always to conceal the very existence of the embedded data.
LSB Steganography is an image steganography technique in which messages are hidden inside an image by replacing each pixel’s least significant bit with the bits of the message to be hidden.
1.Step:
Firstly, we write the code to convert the source image into a NumPy array of pixels and store the size of the image. if image mode equal RGB n value will be 3 or if image mode RGBA n value equal 4 or is not equal any mode n value will be zero. Calculate Total pixel of image.
def encode(src, message, dest):
img = Image.open(src, 'r')
width, height = img.size
array = np.array(list(img.getdata()))
if img.mode == 'RGB':
n = 3
elif img.mode == 'RGBA':
n = 4
else:
n =0
total_pixels = array.size//n
2.Step:
Secondly, we add a delimiter (“$t3g0") at the end of the secret message, so that when the program decodes, it knows when to stop.
message += "$t3g0"
b_message = ''.join([format(ord(i), "08b") for i in message])
req_pixels = len(b_message)
3.Step:
Thirdly, we make a check if the total pixels available is sufficient for the secret message or not.
if req_pixels > total_pixels:
print("ERROR: Need larger file size")
else:
index=0
for p in range(total_pixels):
for q in range(0, 3):
if index < req_pixels:
array[p][q] = int(bin(array[p][q])[2:9] + b_message[index], 2)
index += 1
4.Step:
Finally, we have the updated pixels array and we can use this to create and save it as the destination output image.
array=array.reshape(height, width, n)
enc_img = Image.fromarray(array.astype('uint8'), img.mode)
enc_img.save(dest)
print("Image Encoded Successfully")
1.Step: Firstly, we repeat a similar procedure of saving the pixels of the source image as an array, figuring out the mode, and calculating the total pixels.
def Decode(src):
img = Image.open(src, 'r')
array = np.array(list(img.getdata()))
if img.mode == 'RGB':
n = 3
elif img.mode == 'RGBA':
n = 4
total_pixels = array.size//n
2.Step:
Secondly, we need to extract the least significant bits from each of the pixels starting from the top-left of the image and store it in groups of 8.
hidden_bits = ""
for p in range(total_pixels):
for q in range(0, 3):
hidden_bits += (bin(array[p][q])[2:][-1])
hidden_bits = [hidden_bits[i:i+8] for i in range(0, len(hidden_bits), 8)]
message = ""
for i in range(len(hidden_bits)):
if message[-5:] == "$t3g0":
break
else:
message += chr(int(hidden_bits[i], 2))
Last Step:
Finally, we do a check if the delimiter was found or not. If not, that means there was no hidden message in the image.
if "$t3g0" in message:
print("Hidden Message:", message[:-5])
else:
print("No Hidden Message Found")
encode("TARGET_IMAGE_PATH","YOUR_MESSAGE","DESTINATION_IMAGE_PATH")
decode("DESTINATION_IMAGE_PATH")
14 Dec 31, 2022
0 Jan 13, 2022
3.5k Dec 31, 2022
218 Dec 04, 2022
4 May 16, 2022
12 Jul 30, 2022
1 Jan 03, 2022
88 Nov 29, 2022
1 Oct 29, 2021
152 Dec 13, 2022
2 Oct 21, 2022
11 Aug 22, 2022
1 Dec 23, 2021
3 Dec 29, 2021
2 Jan 01, 2022
20 Dec 16, 2022
350 Jan 02, 2023
133 Dec 27, 2022
146 Dec 23, 2022
1 Aug 16, 2022