对pcap格式的ISCXVPN2016数据集标记为VoIP、Video、Chat、File、Transfer、Browsing这五类，并对其进行加密流量的分类的具体python代码

以下是对pcap格式的ISCXVPN2016数据集进行标记和加密流量分类的Python代码：

import os
import pyshark
import numpy as np
import pandas as pd

# 标记数据包为VoIP、Video、Chat、File、Transfer、Browsing
def label_packet(packet):
    if 'voip' in packet['protocol']:
        return 'VoIP'
    elif 'video' in packet['protocol']:
        return 'Video'
    elif 'chat' in packet['protocol']:
        return 'Chat'
    elif 'file' in packet['protocol']:
        return 'File'
    elif 'transfer' in packet['protocol']:
        return 'Transfer'
    elif 'http' in packet['protocol'] or 'ssl' in packet['protocol']:
        return 'Browsing'
    else:
        return 'Other'

# 加密流量分类
def classify_encrypted_traffic(packets):
    encrypted_packets = 0
    for packet in packets:
        if 'tls' in packet['protocol'] or 'ssl' in packet['protocol']:
            encrypted_packets += 1
    if encrypted_packets / len(packets) >= 0.5:
        return 'Encrypted'
    else:
        return 'Not Encrypted'

# 读取数据集中的pcap文件
def read_pcap_files(folder_path):
    files = os.listdir(folder_path)
    packets = []
    for file in files:
        if file.endswith('.pcap'):
            file_path = os.path.join(folder_path, file)
            pcap = pyshark.FileCapture(file_path)
            for packet in pcap:
                packets.append(packet)
    return packets

# 对数据集进行标记和加密流量分类
def preprocess_dataset(folder_path):
    packets = read_pcap_files(folder_path)
    labels = []
    encrypted_traffic = []
    for packet in packets:
        label = label_packet(packet)
        labels.append(label)
        encrypted_traffic.append(classify_encrypted_traffic(packet.layers))
    df = pd.DataFrame({'Label': labels, 'Encrypted Traffic': encrypted_traffic})
    return df

# 使用示例
folder_path = 'path/to/ISCXVPN2016/dataset'
df = preprocess_dataset(folder_path)
print(df.head())

请注意，这段代码中只是对数据集进行了标记和加密流量分类，并没有进行机器学习模型的训练和测试。如果您需要进行后续的机器学习任务，可以使用标记和加密流量分类后得到的`df`作为输入数据。