LSB算法隐写笔记

由于本人对LSB算法还没有很深刻的体会,这里就简单笔记一下,以后体会深刻了再来补充。

LSB算法

LSB(Least Significant Bit)算法是将秘密信息嵌入到载体图像像素值的最低有效位,也称最不显著位,改变这一位置对载体图像的品质影响最小

加解密脚本,来源于https://github.com/livz/cloacked-pixel/blob/master/lsb.py 。本人进行部分修改,去掉了AES加解密部分,去掉了开头的长度保存,改成了Python3的脚本。

#! /usr/bin/python3
# -*- coding:utf-8 -*-

import sys
import struct
import numpy
import matplotlib.pyplot as plt

from PIL import Image

from Crypto.Cipher import AES

# Decompose a binary file into an array of bits

def decompose(data):
    v = []

    # Pack file len in 4 bytes

    bytes = b""
    for b in data:
        bytes += struct.pack("B", b)

    for b in bytes:
        for i in range(7, -1, -1):
            v.append((b >> i) & 0x1)

    return v

# Assemble an array of bits into a binary file

def assemble(v):
    bytes = b""

    length = len(v)
    for idx in range(0, int(len(v)/8)):
        byte = 0
        for i in range(0, 8):
            if (idx*8+i < length):
                byte = (byte << 1) + v[idx*8+i]
        bytes = bytes + struct.pack("B", byte)

    return bytes

# Set the i-th bit of v to x

def set_bit(n, i, x):
    mask = 1 << i
    n &= ~mask
    if x:
        n |= mask
    return n

# Embed payload file into LSB bits of an image

def embed(imgFile, payload):
    # Process source image
    img = Image.open(imgFile)
    (width, height) = img.size
    conv = img.convert("RGBA").getdata()
    print("[*] Input image size: %dx%d pixels." % (width, height))
    max_size = width*height*3.0/8/1024        # max payload size
    print("[*] Usable payload size: %.2f KB." % (max_size))

    f = open(payload, "rb")
    data = f.read()
    f.close()
    print("[+] Payload size: %.3f KB " % (len(data)/1024.0))

    # Process data from payload file
    v = decompose(data)

    # Add until multiple of 3
    while(len(v) % 3):
        v.append(0)

    payload_size = len(v)/8/1024.0
    print("[+] Encrypted payload size: %.3f KB " % (payload_size))
    if (payload_size > max_size - 4):
        print("[-] Cannot embed. File too large")
        sys.exit()

    # Create output image
    steg_img = Image.new('RGBA', (width, height))
    data_img = steg_img.getdata()

    idx = 0

    for h in range(height):
        for w in range(width):
            (r, g, b, a) = conv.getpixel((w, h))
            if idx < len(v):
                r = set_bit(r, 0, v[idx])
                g = set_bit(g, 0, v[idx+1])
                b = set_bit(b, 0, v[idx+2])
            data_img.putpixel((w, h), (r, g, b, a))
            idx = idx + 3

    steg_img.save(imgFile + "-stego.png", "PNG")

    print("[+] %s embedded successfully!" % payload)

# Extract data embedded into LSB of the input file

def extract(in_file, out_file):
    # Process source image
    img = Image.open(in_file)
    (width, height) = img.size
    conv = img.convert("RGBA").getdata()
    print("[+] Image size: %dx%d pixels." % (width, height))

    # Extract LSBs
    v = []
    for h in range(height):
        for w in range(width):
            (r, g, b, a) = conv.getpixel((w, h))
            v.append(r & 1)
            v.append(g & 1)
            v.append(b & 1)

    data_out = assemble(v)

    # Write data
    out_f = open(out_file, "wb")
    out_f.write(data_out)
    out_f.close()

    print("[+] Written extracted data to %s." % out_file)

# Statistical analysis of an image to detect LSB steganography

def analyse(in_file):
    '''
    - Split the image into blocks.
    - Compute the average value of the LSBs for each block.
    - The plot of the averages should be around 0.5 for zones that contain
      hidden encrypted messages (random data).
    '''
    BS = 100  # Block size
    img = Image.open(in_file)
    (width, height) = img.size
    print("[+] Image size: %dx%d pixels." % (width, height))
    conv = img.convert("RGBA").getdata()

    # Extract LSBs
    vr = []  # Red LSBs
    vg = []  # Green LSBs
    vb = []  # LSBs
    for h in range(height):
        for w in range(width):
            (r, g, b, a) = conv.getpixel((w, h))
            vr.append(r & 1)
            vg.append(g & 1)
            vb.append(b & 1)

    # Average colours' LSB per each block
    avgR = []
    avgG = []
    avgB = []
    for i in range(0, len(vr), BS):
        avgR.append(numpy.mean(vr[i:i + BS]))
        avgG.append(numpy.mean(vg[i:i + BS]))
        avgB.append(numpy.mean(vb[i:i + BS]))

    # Nice plot
    numBlocks = len(avgR)
    blocks = [i for i in range(0, numBlocks)]
    plt.axis([0, len(avgR), 0, 1])
    plt.ylabel('Average LSB per block')
    plt.xlabel('Block number')

#    plt.plot(blocks, avgR, 'r.')
#    plt.plot(blocks, avgG, 'g')
    plt.plot(blocks, avgB, 'bo')

    plt.show()

def usage(progName):
    print("LSB steganogprahy. Hide files within least significant bits of images.\n")
    print("Usage:")
    print("  %s hide  " % progName)
    print("  %s extract  " % progName)
    print("  %s analyse " % progName)
    sys.exit()

if __name__ == "__main__":
    if len(sys.argv) < 3:
        usage(sys.argv[0])

    if sys.argv[1] == "hide":
        embed(sys.argv[2], sys.argv[3])
    elif sys.argv[1] == "extract":
        extract(sys.argv[2], sys.argv[3])
    elif sys.argv[1] == "analyse":
        analyse(sys.argv[2])
    else:
        print("[-] Invalid operation specified")

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