Update ghost_engine_configs.py

ghost_engine_configs.py

@@ -62,6 +62,35 @@ BASE_HOMOGLYPH_RATIO = 0.15
 # This value is scaled by the poison strength
 MAX_BYTE_PERTURBATION = 7
 
+# -----------------
+# Image Protection (Invisible Armor) Settings
+# -----------------
+
+# CRITICAL: Mid-band frequency targeting for maximum ML disruption
+# Mid-band (normalized radius 0.10-0.40) is where CNNs are most vulnerable
+# because it disrupts edge detection and feature extraction layers
+
+# Target mid-band energy ratio (0.0 to 1.0)
+# Higher values = more ML disruption, less human visibility impact
+# Recommended: 0.70-0.90 for optimal ML poisoning
+TARGET_MID_BAND_ENERGY = 0.85
+
+# Low-band energy ratio (0.0 to 1.0)
+# Low frequencies (< 0.10 radius) carry semantic/shape information
+# Keep minimal to preserve human perception
+TARGET_LOW_BAND_ENERGY = 0.05
+
+# High-band energy ratio (0.0 to 1.0)
+# High frequencies (> 0.40 radius) are fine details/noise
+# Keep minimal as they're easily removed by compression
+TARGET_HIGH_BAND_ENERGY = 0.10
+
+# Default image protection strength (1.0 to 5.0)
+# 1.0 = Invisible to humans, moderate AI disruption
+# 3.0 = Barely visible, strong AI disruption (70%+ mid-band)
+# 5.0 = Slight artifacts, maximum AI confusion (85%+ mid-band)
+DEFAULT_IMAGE_ARMOR_STRENGTH = 3.0
+
 # -----------------
 # Advanced Configuration
 # -----------------
@@ -77,6 +106,11 @@ GHOST_CONFIG: Dict[str, Any] = {
     "default_poison_type": DEFAULT_POISON_TYPE,
     "base_homoglyph_ratio": BASE_HOMOGLYPH_RATIO,
     "max_byte_perturbation": MAX_BYTE_PERTURBATION,
+    # Image armor frequency targets
+    "target_mid_band_energy": TARGET_MID_BAND_ENERGY,
+    "target_low_band_energy": TARGET_LOW_BAND_ENERGY,
+    "target_high_band_energy": TARGET_HIGH_BAND_ENERGY,
+    "default_image_armor_strength": DEFAULT_IMAGE_ARMOR_STRENGTH,
 }
 
 def get_config(key: str) -> Any: