Fix small bug on concealment_ae_module to save the scaler and trained model

Fixed a dependency issue with keras, tensorflow, and pyyaml-include

Author: afmurillo

dhalsim/network_attacks/concealment_ae_model.py

@@ -72,13 +72,12 @@ def load_scaler(self, scaler_path):
         print('Scaler loaded')
 
     # Saves the model and the scaler used to train the model
-    def save_model(self, filename):
-        print('saving trained model at: ', str(filename))
-        self.generator.save(str(filename))
+    def save_model(self, model_filename, scaler_filename):
+        print('saving trained model at: ', str(model_filename))
+        self.generator.save(str(model_filename))
 
-        scaler_path = Path.cwd()
-        print('saved scaler model at: ', scaler_path)
-        joblib.dump(self.attacker_scaler, 'ctown_attacker_scaler.gz')
+        print('saved scaler model at: ', scaler_filename)
+        joblib.dump(self.attacker_scaler, scaler_filename)
 
     def init_generator(self, training_path):
         # Load and preprocess training data

dhalsim/network_attacks/unconstrained_blackbox_netfilter_queue.py

@@ -101,7 +101,8 @@ def __init__(self,  intermediate_yaml_path: Path, yaml_index: int, queue_number:
             self.advAE.train_model(file_expr)
             self.logger.info('Model trained')
             ctown_model = Path(__file__).parent/'adversarial_models/ctown_generator_100_percent'
-            self.advAE.save_model(ctown_model)
+            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:

setup.py

@@ -16,7 +16,7 @@
     packages=['dhalsim'],
     install_requires=[
         'pyyaml==6.0.1',
-        'pyyaml-include',
+        'pyyaml-include==1.4.1',
         'antlr4-python3-runtime==4.13.1',
         'progressbar2',
         'numpy==1.24.3',
@@ -33,7 +33,7 @@
         'pytest',
         'tensorflow',
         'scikit-learn',
-        'keras',
+        'keras==2.13.1',
         'pytest',
         'pytest-mock',
         'mock'