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diff --git a/evaluate/CICIDS2017.py b/evaluate/CICIDS2017.py
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+++ b/evaluate/CICIDS2017.py
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+import torch
+from torch.utils.data import Dataset
+import numpy as np
+import pandas as pd
+
+"""
+CICIDS2017s数据集，提取统计特征
+"""
+class CICIDS2017Statistic():
+    def __init__(self):
+        print("CICIDS2017 Statistic Init")
+        self.config =  {
+    # "Benign": {
+    #     "path": '/home/sunhanwu/datasets/cicids2017/MachineLearningCVE/Friday-WorkingHours-Morning.pcap_ISCX.csv',
+    #     "label": ['BENIGN'],
+    #     "tag": 0
+    # },
+    "Botnet": {
+        "path": '/home/sunhanwu/datasets/cicids2017/MachineLearningCVE/Friday-WorkingHours-Morning.pcap_ISCX.csv',
+        'label': ['Bot'],
+        'tag': 1,
+        'num': 1966
+    },
+    "Fuzzing": {
+        "path": '/home/sunhanwu/datasets/cicids2017/MachineLearningCVE/Wednesday-workingHours.pcap_ISCX.csv',
+        'label': ['DoS Hulk'],
+        'tag': 2,
+        'num': 10000
+    },
+    "PortScan": {
+        "path": '/home/sunhanwu/datasets/cicids2017/MachineLearningCVE/Friday-WorkingHours-Afternoon-PortScan.pcap_ISCX.csv',
+        'label': ['PortScan'],
+        'tag': 3,
+        'num': 10000
+    },
+    "BruteForce": {
+        "path": '/home/sunhanwu/datasets/cicids2017/MachineLearningCVE/Tuesday-WorkingHours.pcap_ISCX.csv',
+        'label': ['FTP-Patator', 'SSH-Patator'],
+        'tag': 4,
+        'num': 10000
+    },
+    "DDoS": {
+        "path": '/home/sunhanwu/datasets/cicids2017/MachineLearningCVE/Friday-WorkingHours-Afternoon-DDos.pcap_ISCX.csv',
+        'label': ['DDoS'],
+        'tag': 5,
+        'num': 10000
+    }
+}
+        self.load_data()
+
+    def load_data(self):
+        self.data = {}
+        for cls in self.config:
+            print("load data from {}".format(self.config[cls]['path']))
+            data = pd.read_csv(self.config[cls]['path'])
+            benign = data[data[' Label'] == 'BENIGN']
+            benign[' Label'] = 0
+            benign = benign.iloc[:self.config[cls]['num'], 1:]
+            malware = data[data[' Label'].isin(self.config[cls]['label'])]
+            malware.loc[malware[' Label'].isin(self.config[cls]['label']), ' Label'] = self.config[cls]['tag']
+            malware = malware.iloc[:self.config[cls]['num'], 1:]
+            self.data[cls] = np.vstack([benign, malware])
+            np.save("/home/sunhanwu/datasets/cicids2017/npy/" + cls + ".npy", self.data[cls])
+            print("{} done: total num {}".format(cls, len(self.data[cls])))
+    def __getitem__(self, item):
+        pass
+
+    def __len__(self):
+        pass
+
+
+"""
+CICIDS2017s数据集，提取序列特征
+"""
+class CICIDS2017_Sequence(Dataset):
+    def __init__(self):
+        print("test 2")
+        pass
+
+    def __getitem__(self, item):
+        pass
+
+    def __len__(self):
+        pass
+
+if __name__ == '__main__':
+    D = CICIDS2017Statistic()
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