Update watermark_detection.py

watermark_detection.py

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+# watermark_detection.py
+
+# Import necessary libraries
+import numpy as np
+import tensorflow as tf  # Assuming TensorFlow is used
+
+# Function to detect and extract watermark from the model
+def detect_watermark(model, test_data):
+    # Load the model (assuming 'model' is the loaded model)
+
+    # Example pseudocode to demonstrate watermark detection
+    watermark_detected = False
+    watermark = None
+
+    # Check specific layers or parameters that might contain the watermark
+    # For example, if the watermark was embedded in certain weights or biases
+
+    # Access a specific layer (example: last layer)
+    watermark_layer = model.layers[-1]  # Accessing the last layer as an example
+
+    # Get the weights of the layer
+    layer_weights = watermark_layer.get_weights()
+
+    # Analyze the weights or specific parameters for watermark presence
+    # Example: Check if the weights contain a specific pattern or information
+    # Note: This logic depends on the method used for watermark embedding
+    # Here, assuming watermark is embedded as a specific value in weights
+    watermark_value = 1.0  # Example watermark value
+
+    # Extract the watermark if the pattern or value is detected in the weights
+    if watermark_value in layer_weights[0]:  # Considering only the first weight matrix for simplicity
+        watermark_detected = True
+        watermark = "Watermark detected in layer weights!"
+
+    return watermark_detected, watermark
+
+# Example usage
+if __name__ == "__main__":
+    # Load your trained model and test data
+    # Example: Load model and test data
+    model = tf.keras.models.load_model('path_to_your_model')
+    test_data = np.random.random((100, 10))  # Example test data
+
+    # Call the watermark detection function with your loaded model and test data
+    detected, extracted_watermark = detect_watermark(model, test_data)
+
+    # Print detection results
+    print("Watermark Detected:", detected)
+    if detected:
+        print("Extracted Watermark:", extracted_watermark)