Add entropy-based evaluate scripts for CARLA and MIRGU

CARLA_Entropy/config_dos_CARLA.yaml

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+run_steps:
+  attack: True
+  decode: True
+  evaluate: True
+  update: True
+
+
+attack:
+  original_test_dir: "CARLA_dataset/DoS/Surrogate/test_images"
+  original_label_file: "CARLA_dataset/DoS/Surrogate/test_labels.txt"
+  original_tracksheet: "CARLA_dataset/DoS/Surrogate/test_track.csv"
+  surrogate_model: "Trained_models/densenet161_surrogate_CARLA_DoS.pth"
+  output_dir: "perturbed_images_dos_CARLA"
+
+decode:
+  decoded_output_dir: "decoded_traffic_dos_CARLA"
+
+evaluate:
+  model_path: "Trained_models/CARLA_DoS_og_final_model.h5"
+  prediction_output_dir: "prediction_output_dos_CARLA"
+
+update:
+  tracksheet_dir: "tracksheets_CARLA"

CARLA_Entropy/config_spoof_CARLA.yaml

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+run_steps:
+  attack: True
+  decode: True
+  evaluate: True
+  update: True
+
+
+attack:
+  original_test_dir: "CARLA_dataset/Spoof/Surrogate/merged_targated_Spoof_attack_images"
+  original_label_file: "CARLA_dataset/Spoof/Surrogate/test_labels.txt"
+  original_tracksheet: "CARLA_dataset/Spoof/Surrogate/test_track.csv"
+  surrogate_model: "Trained_models/densenet161_surrogate_CARLA_Spoof.pth"
+  output_dir: "perturbed_images_spoof_CARLA"
+
+decode:
+  decoded_output_dir: "decoded_traffic_spoof_CARLA"
+
+evaluate:
+  model_path: "Trained_models/CARLA_Spoof_og_final_model.h5"
+  prediction_output_dir: "prediction_output_spoof_CARLA"
+
+update:
+  tracksheet_dir: "tracksheets_CARLA"

CARLA_Entropy/driver_dos_CARLA.py

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+import os
+
+import sys
+import yaml
+import argparse
+from io import StringIO
+
+
+# -------------------------------------------------
+# Load YAML Config
+# -------------------------------------------------
+def load_config(path):
+    with open(path, "r") as f:
+        return yaml.safe_load(f)
+
+
+# -------------------------------------------------
+# Main Pipeline
+# -------------------------------------------------
+def pipeline_run(config):
+
+    round_num = config["round"]
+    steps = config.get("run_steps", {})
+
+    print(f"\n==============================")
+    print(f"Running Round in driver file {round_num}")
+    print(f"==============================")
+
+    # ==========================================================
+    # STEP 1: ATTACK
+    # ==========================================================
+    if steps.get("attack", False):
+
+        from scripts.adversarial_attack_dos_final_CARLA import run as run_attack
+
+        round_num = config["round"]
+
+        # Copy base attack config
+        attack_cfg = config["attack"].copy()
+
+        # Required keys for attack script
+        attack_cfg["output_path"] = config["attack"]["output_dir"]
+        attack_cfg["model_path"] = config["attack"]["surrogate_model"]
+        attack_cfg["rounds"] = round_num
+
+        # Round-dependent logic
+        if round_num == 0:
+            attack_cfg["test_data_dir"] = config["attack"]["original_test_dir"]
+            attack_cfg["packet_level_data"] = config["attack"]["original_tracksheet"]
+            attack_cfg["test_label_file"] = config["attack"]["original_label_file"]
+        else:
+            attack_cfg["test_data_dir"] = config["attack"]["output_dir"]
+            attack_cfg["packet_level_data"] = (
+                f'{config["update"]["tracksheet_dir"]}/dos_test_track_{round_num-1}.csv'
+            )
+            attack_cfg["test_label_file"] = (
+                f'{config["attack"]["output_dir"]}/labels_{round_num}.txt'
+            )
+
+        # ---------------------------------------------------
+        # Create output directory
+        # ---------------------------------------------------
+        attack_out = attack_cfg["output_path"]
+        os.makedirs(attack_out, exist_ok=True)
+
+        print("\n=== Step 1: Adversarial Attack ===")
+
+        # ---------------------------------------------------
+        # Capture stdout and save to stats file
+        # ---------------------------------------------------
+        stats_file = os.path.join(attack_out, f"stats_round_{round_num}.txt")
+
+        old_stdout = sys.stdout
+        sys.stdout = mystream = StringIO()
+
+        try:
+            run_attack(attack_cfg)
+        finally:
+            sys.stdout = old_stdout
+
+        with open(stats_file, "w") as f:
+            f.write(mystream.getvalue())
+
+        print(f"[INFO] Attack log saved to {stats_file}")
+
+
+
+    # ==========================================================
+    # STEP 2: DECODE
+    # ==========================================================
+    if steps.get("decode", False):
+
+        from scripts.Traffic_decoder_dos_CARLA import run as run_decode
+
+        decode_cfg = config["decode"].copy()
+        decode_cfg["rounds"] = round_num
+        decode_cfg["input_images"] = config["attack"]["output_dir"]
+        decode_cfg["csv_file"] = (
+            f'{config["attack"]["output_dir"]}/packet_level_data_{round_num}.csv'
+        )
+        decode_cfg["output_file"] = (
+            f'{config["decode"]["decoded_output_dir"]}/traffic_{round_num}.txt'
+        )
+
+        os.makedirs(config["decode"]["decoded_output_dir"], exist_ok=True)
+
+        print("\n=== Step 2: Traffic Decoder ===")
+        run_decode(decode_cfg)
+
+
+    # ==========================================================
+    # STEP 3: EVALUATION
+    # ==========================================================
+    if steps.get("evaluate", False):
+
+        from scripts.evaluate_dos_CARLA import run as run_eval
+
+        eval_cfg = config["evaluate"].copy()
+        eval_cfg["rounds"] = round_num
+        eval_cfg["model_path"] = config["evaluate"]["model_path"]
+        eval_cfg["traffic_path"] = (
+            f'{config["decode"]["decoded_output_dir"]}/traffic_{round_num}.txt'
+        )
+        eval_cfg["tracksheet"] = (
+            f'{config["attack"]["output_dir"]}/packet_level_data_{round_num}.csv'
+        )
+        eval_cfg["output_path"] = (
+            f'{config["evaluate"]["prediction_output_dir"]}/prediction_output_{round_num}.csv'
+        )
+
+        os.makedirs(config["evaluate"]["prediction_output_dir"], exist_ok=True)
+
+        print("\n=== Step 3: Evaluation ===")
+        run_eval(eval_cfg)
+
+
+    # ==========================================================
+    # STEP 4: UPDATE
+    # ==========================================================
+    if steps.get("update", False):
+
+        from scripts.update_labels_dos_CARLA import run as run_update
+
+        update_cfg = config["update"].copy()
+
+        update_cfg["tracksheet"] = (
+            f'{config["update"]["tracksheet_dir"]}/dos_test_track_{round_num}.csv'
+        )
+
+        # Label logic
+        update_cfg["label_file"] = config["attack"]["original_label_file"]
+
+        update_cfg["updated_label_file"] = (
+            f'{config["attack"]["output_dir"]}/labels_{round_num+1}.txt'
+        )
+
+        print("\n=== Step 4: Update Labels ===")
+        run_update(update_cfg)
+
+
+
+# -------------------------------------------------
+# MAIN
+# -------------------------------------------------
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--round", type=int, default=0)
+    parser.add_argument("--config", type=str, default="config_dos_CARLA.yaml")
+    args = parser.parse_args()
+
+    cfg = load_config(args.config)
+    cfg["round"] = args.round
+
+    pipeline_run(cfg)

CARLA_Entropy/driver_spoof_CARLA.py

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+import os
+
+import sys
+import yaml
+import argparse
+from io import StringIO
+
+
+# -------------------------------------------------
+# Load YAML Config
+# -------------------------------------------------
+def load_config(path):
+    with open(path, "r") as f:
+        return yaml.safe_load(f)
+
+
+# -------------------------------------------------
+# Main Pipeline
+# -------------------------------------------------
+def pipeline_run(config):
+
+    round_num = config["round"]
+    steps = config.get("run_steps", {})
+
+    print(f"\n==============================")
+    print(f"Running Round in driver file {round_num}")
+    print(f"==============================")
+
+    # ==========================================================
+    # STEP 1: ATTACK
+    # ==========================================================
+    if steps.get("attack", False):
+
+        from scripts.adversarial_attack_spoof_CARLA import run as run_attack
+
+        round_num = config["round"]
+
+        # Copy base attack config
+        attack_cfg = config["attack"].copy()
+
+        # Required keys for attack script
+        attack_cfg["output_path"] = config["attack"]["output_dir"]
+        attack_cfg["model_path"] = config["attack"]["surrogate_model"]
+        attack_cfg["rounds"] = round_num
+
+        # Round-dependent logic
+        if round_num == 0:
+            attack_cfg["test_data_dir"] = config["attack"]["original_test_dir"]
+            attack_cfg["packet_level_data"] = config["attack"]["original_tracksheet"]
+            attack_cfg["test_label_file"] = config["attack"]["original_label_file"]
+        else:
+            attack_cfg["test_data_dir"] = config["attack"]["output_dir"]
+            attack_cfg["packet_level_data"] = (
+                f'{config["update"]["tracksheet_dir"]}/spoof_test_track_{round_num-1}.csv'
+            )
+            attack_cfg["test_label_file"] = (
+                f'{config["attack"]["output_dir"]}/labels_{round_num}.txt'
+            )
+
+        # ---------------------------------------------------
+        # Create output directory
+        # ---------------------------------------------------
+        attack_out = attack_cfg["output_path"]
+        os.makedirs(attack_out, exist_ok=True)
+
+        print("\n=== Step 1: Adversarial Attack ===")
+
+        # ---------------------------------------------------
+        # Capture stdout and save to stats file
+        # ---------------------------------------------------
+        stats_file = os.path.join(attack_out, f"stats_round_{round_num}.txt")
+
+        old_stdout = sys.stdout
+        sys.stdout = mystream = StringIO()
+
+        try:
+            run_attack(attack_cfg)
+        finally:
+            sys.stdout = old_stdout
+
+        with open(stats_file, "w") as f:
+            f.write(mystream.getvalue())
+
+        print(f"[INFO] Attack log saved to {stats_file}")
+
+
+
+    # ==========================================================
+    # STEP 2: DECODE
+    # ==========================================================
+    if steps.get("decode", False):
+
+        from scripts.Traffic_decoder_spoof_CARLA import run as run_decode
+
+        decode_cfg = config["decode"].copy()
+        decode_cfg["rounds"] = round_num
+        decode_cfg["input_images"] = config["attack"]["output_dir"]
+        decode_cfg["csv_file"] = (
+            f'{config["attack"]["output_dir"]}/packet_level_data_{round_num}.csv'
+        )
+        decode_cfg["output_file"] = (
+            f'{config["decode"]["decoded_output_dir"]}/traffic_{round_num}.txt'
+        )
+
+        os.makedirs(config["decode"]["decoded_output_dir"], exist_ok=True)
+
+        print("\n=== Step 2: Traffic Decoder ===")
+        run_decode(decode_cfg)
+
+
+    # ==========================================================
+    # STEP 3: EVALUATION
+    # ==========================================================
+    if steps.get("evaluate", False):
+
+        from scripts.evaluate_spoof_CARLA import run as run_eval
+
+        eval_cfg = config["evaluate"].copy()
+        eval_cfg["rounds"] = round_num
+        eval_cfg["model_path"] = config["evaluate"]["model_path"]
+        eval_cfg["traffic_path"] = (
+            f'{config["decode"]["decoded_output_dir"]}/traffic_{round_num}.txt'
+        )
+        eval_cfg["tracksheet"] = (
+            f'{config["attack"]["output_dir"]}/packet_level_data_{round_num}.csv'
+        )
+        eval_cfg["output_path"] = (
+            f'{config["evaluate"]["prediction_output_dir"]}/prediction_output_{round_num}.csv'
+        )
+
+        os.makedirs(config["evaluate"]["prediction_output_dir"], exist_ok=True)
+
+        print("\n=== Step 3: Evaluation ===")
+        run_eval(eval_cfg)
+
+
+    # ==========================================================
+    # STEP 4: UPDATE
+    # ==========================================================
+    if steps.get("update", False):
+
+        from scripts.update_labels_spoof_CARLA import run as run_update
+
+        update_cfg = config["update"].copy()
+
+        update_cfg["tracksheet"] = (
+            f'{config["update"]["tracksheet_dir"]}/spoof_test_track_{round_num}.csv'
+        )
+
+        # Label logic
+        update_cfg["label_file"] = config["attack"]["original_label_file"]
+
+        update_cfg["updated_label_file"] = (
+            f'{config["attack"]["output_dir"]}/labels_{round_num+1}.txt'
+        )
+
+        print("\n=== Step 4: Update Labels ===")
+        run_update(update_cfg)
+
+
+
+# -------------------------------------------------
+# MAIN
+# -------------------------------------------------
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--round", type=int, default=0)
+    parser.add_argument("--config", type=str, default="config_spoof_CARLA.yaml")
+    args = parser.parse_args()
+
+    cfg = load_config(args.config)
+    cfg["round"] = args.round
+
+    pipeline_run(cfg)