updated code

Author: desktop machine

dhalsim/network_attacks/concealment_ae_model.py

@@ -87,7 +87,7 @@ def init_generator(self, training_path):
 
         # Adversarial model for concealment
         # toDo: Ask about this parameter
-        hide_layers = 39
+        hide_layers = 160
         self.hide_layers = hide_layers
         self.generator_layers = [self.feature_dims,
                                 int(self.hide_layers / 2),

dhalsim/network_attacks/unconstrained_blackbox_netfilter_queue.py

@@ -86,30 +86,27 @@ def __init__(self,  intermediate_yaml_path: Path, yaml_index: int, queue_number:
 
         # Adversarial model for concealment
         self.advAE = ConcealmentAE(self.scada_tags)
+        ctown_model = Path(__file__).parent/'adversarial_models/ctown_generator_100_percent'
+        scaler_path = Path(__file__).parent/'adversarial_models/ctown_attacker_scaler.gz'
 
         try:
             # For now, only c-town is supported    
-            ctown_model = Path(__file__).parent/'adversarial_models/ctown_generator_100_percent'
             self.advAE.generator = load_model(str(ctown_model))
-
-            scaler_path = Path(__file__).parent/'adversarial_models/ctown_attacker_scaler.gz'
             self.advAE.load_scaler(scaler_path)
             self.logger.debug('Trained model found')
 
         except FileNotFoundError:
             self.logger.info('No trained model found, training...')
             self.advAE.train_model(file_expr)
             self.logger.info('Model trained')
-            ctown_model = Path(__file__).parent/'adversarial_models/ctown_generator_100_percent'
-            scaler_path = Path(__file__).parent/'adversarial_models/ctown_attacker_scaler.gz'
             self.advAE.save_model(ctown_model, scaler_path)
             self.logger.info('Model saved')
 
         except IOError:
             self.logger.info('No trained model found, training...')
             self.advAE.train_model(file_expr)
             self.logger.info('Model trained')
-            self.advAE.save_model(ctown_model)
+            self.advAE.save_model(ctown_model, scaler_path)
             self.logger.info('Model saved')
 
         self.sync_flag = True