Update CIC-IDS2017.py

CIC-IDS2017.py

@@ -1,116 +1,60 @@
 import os
-import datasets
 import pandas as pd
-
+import datasets
 
 _CITATION = """\
-@article{maharajan2020attack,
-  title={Attack classification and intrusion detection in IoT network using machine learning techniques},
-  author={Maharajan, R and Raja, KS},
-  journal={Computers \& Electrical Engineering},
-  volume={87},
-  pages={106783},
-  year={2020},
-  publisher={Elsevier}
-}"""
+@InProceedings{YourReferenceHere,
+}
+"""
 
 _DESCRIPTION = """\
-The CIC-IDS2017 dataset is an intrusion detection dataset that consists of network traffic data. \
-It contains different network attacks and normal traffic. This dataset can be used for evaluating \
-intrusion detection systems in IoT networks.
+Description of your dataset.
 """
 
-_HOMEPAGE = "https://www.unb.ca/cic/datasets/ids-2017.html"
-
-_LICENSE = "Unknown"
+_HOMEPAGE = "https://dataset-homepage/"
+_LICENSE = "Dataset License"
 
-_FOLDERS = {
-    "Network-Flows": "Network-Flows",
-    "Packet-Fields": "Packet-Fields",
-    "Packet-Bytes": "Packet-Bytes",
-    "Payload-Bytes": "Payload-Bytes",
+_URLS = {
+    "Network-Flows": "Network-Flows/CICIDS_Flow.csv",
+    "Packet-Fields": "Packet-Fields/Packet_Fields_File_10.csv",
+    "Packet-Bytes": "Packet-Bytes/Packet_Bytes_File_10.csv",
+    "Payload-Bytes": "Payload-Bytes/Payload_Bytes_File_10.csv",
 }
 
 
-class CICIDS2017(datasets.GeneratorBasedBuilder):
+class YourDataset(datasets.GeneratorBasedBuilder):
+
     VERSION = datasets.Version("1.0.0")
 
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="Network-Flows", version=VERSION, description="Folder 1 of CIC-IDS2017 dataset"),
-        datasets.BuilderConfig(name="Packet-Fields", version=VERSION, description="Folder 2 of CIC-IDS2017 dataset"),
-        datasets.BuilderConfig(name="Packet-Bytes", version=VERSION, description="Folder 3 of CIC-IDS2017 dataset"),
-        datasets.BuilderConfig(name="Payload-Bytes", version=VERSION, description="Folder 4 of CIC-IDS2017 dataset"),
+        datasets.BuilderConfig(name=config_name, version=VERSION, description=f"This part of my dataset covers {config_name}")
+        for config_name in _URLS.keys()
     ]
 
-    DEFAULT_CONFIG_NAME = "Network-Flows"
-
     def _info(self):
-        if self.config.name == "Network-Flows":
-            features = datasets.Features(
-                {
-                    "flow_id": datasets.Value("int64"),
-                    "source_ip": datasets.Value("string"),
-                    # Add more features specific to folder_1 configuration
-                }
-            )
-        elif self.config.name == "Packet-Fields":
-            features = datasets.Features(
-                {
-                    "flow_id": datasets.Value("int64"),
-                    "packet_id": datasets.Value("int64"),
-                    # Add more features specific to folder_2 configuration
-                }
-            )
-        elif self.config.name == "Packet-Bytes":
-            features = datasets.Features(
-                {
-                    "flow_id": datasets.Value("int64"),
-                    "packet_id": datasets.Value("int64"),
-                    # Add more features specific to folder_3 configuration
-                }
-            )
-        else:  # folder_4
-            features = datasets.Features(
-                {
-                    "flow_id": datasets.Value("int64"),
-                    "packet_id": datasets.Value("int64"),
-                    # Add more features specific to folder_4 configuration
-                }
-            )
-
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
-            features=features,
+            features=datasets.Features({
+                # TODO: Adjust features according to your dataset
+                "flow_id": datasets.Value("int64"),
+                "attack_label": datasets.Value("string"),
+                # More columns...
+            }),
             homepage=_HOMEPAGE,
             license=_LICENSE,
             citation=_CITATION,
         )
 
     def _split_generators(self, dl_manager):
-        folder_path = _FOLDERS[self.config.name]
-        data_dir = dl_manager.download(folder_path)
-        csv_files = [
-            filename for filename in os.listdir(data_dir) if filename.endswith(".csv")
-        ]
-
+        url = os.path.join(self.config.data_dir, _URLS[self.config.name])
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
-                gen_kwargs={"data_dir": data_dir, "csv_files": csv_files},
-            )
+                gen_kwargs={"filepath": url},
+            ),
         ]
 
-    def _generate_examples(self, data_dir, csv_files):
-        for csv_file in csv_files:
-            file_path = os.path.join(data_dir, csv_file)
-            df = pd.read_csv(file_path)
-            for idx, row in df.iterrows():
-                example = {
-                    "source_ip": row["source_ip"],
-                    "destination_ip": row["destination_ip"],
-                    "timestamp": row["timestamp"],
-                    "protocol": row["protocol"],
-                    "flow_duration": row["flow_duration"],
-                    # Add more feature values according to the dataset columns
-                }
-                yield idx, example
+    def _generate_examples(self, filepath):
+        df = pd.read_csv(filepath)
+        for id_, row in df.iterrows():
+            yield id_, row.to_dict()