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import streamlit as st
from PIL import Image
import numpy as np
def steganography_detection():
def lsb_analysis(image):
"""
Analyzes the Least Significant Bits (LSB) of the image pixels
and checks for irregularities that might indicate hidden data.
"""
img = Image.open(image)
img = img.convert('RGB') # Ensure RGB mode
pixels = np.array(img) # Convert image to numpy array
if len(pixels.shape) != 3 or pixels.shape[2] != 3:
raise ValueError("Unsupported image format. Please use RGB images.")
height, width, _ = pixels.shape
lsb_count = [0, 0] # Count of 0s and 1s in the LSB
lsb_distribution = []
# Loop through each pixel and channel
for y in range(height):
for x in range(width):
pixel = pixels[y, x]
for channel in range(3): # Process R, G, B channels
lsb = pixel[channel] & 1
lsb_count[lsb] += 1
lsb_distribution.append(lsb)
total_lsb = sum(lsb_count)
if total_lsb == 0:
return None, None
# Compute percentage distribution
lsb_percentage = [count / total_lsb * 100 for count in lsb_count]
return lsb_percentage, lsb_distribution
st.title("Steganography Detection Tool")
st.subheader("Analyze images for hidden messages based on LSB irregularities")
uploaded_image = st.file_uploader("Upload an image to analyze", type=["png", "jpg", "jpeg"])
analyze_button = st.button("Analyze Image")
if analyze_button:
if uploaded_image:
try:
st.image(uploaded_image, caption="Uploaded Image", use_column_width=True)
lsb_percentage, lsb_distribution = lsb_analysis(uploaded_image)
if lsb_percentage is None:
st.error("Unable to analyze the image.")
else:
st.write("### LSB Distribution Analysis")
st.write(f"**Percentage of LSBs:**\n- 0s: {lsb_percentage[0]:.2f}%\n- 1s: {lsb_percentage[1]:.2f}%")
# Visualization
st.write("### Visualization of LSB Distribution")
st.bar_chart({
"LSB Values": ["0s", "1s"],
"Percentage": lsb_percentage
})
# Detection threshold
threshold = 50 # Typically, natural images have an approximately equal distribution of 0s and 1s
if abs(lsb_percentage[0] - lsb_percentage[1]) > 5:
st.warning("The image shows irregular LSB distribution, suggesting possible steganographic modification.")
else:
st.success("The LSB distribution appears normal, with no clear indication of hidden data.")
except Exception as e:
st.error(f"An error occurred while analyzing the image: {e}")
else:
st.error("Please upload an image for analysis.")
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