# 示例：使用机器学习的简单异常检测
from sklearn.ensemble import IsolationForest

# 示例网络流量数据
network_data = [
    {'packet_size': 100, 'frequency': 10},
    {'packet_size': 150, 'frequency': 12},
    # ... 更多数据
]

# 训练Isolation Forest模型
model = IsolationForest(contamination=0.01)
model.fit(network_data)

# 检测异常
anomalies = model.predict(network_data)

# 示例：使用NLP检测钓鱼邮件
from transformers import pipeline

# 加载预训练的NLP模型
nlp = pipeline("text-classification")

# 示例邮件内容
email_content = """
主题：紧急：您的账户将被暂停

尊敬的客户，

您的账户已被标记为存在可疑活动。请立即点击以下链接验证您的身份：

http://suspicious-link.com

24小时内未验证将导致账户暂停。

此致，
客户支持
"""

# 对邮件进行分类
result = nlp(email_content)
print(result)

# Example: Simple anomaly detection using machine learning
from sklearn.ensemble import IsolationForest

# Sample network traffic data
network_data = [
    {'packet_size': 100, 'frequency': 10},
    {'packet_size': 150, 'frequency': 12},
    # ... more data
]

# Train an Isolation Forest model
model = IsolationForest(contamination=0.01)
model.fit(network_data)

# Detect anomalies
anomalies = model.predict(network_data)

# Example: Using NLP to detect phishing emails
from transformers import pipeline

# Load a pre-trained NLP model
nlp = pipeline("text-classification")

# Sample email content
email_content = """
Subject: Urgent: Your Account Will Be Suspended

Dear Customer,

Your account has been flagged for suspicious activity. Please click the link below to verify your identity immediately:

http://suspicious-link.com

Failure to verify within 24 hours will result in account suspension.

Best regards,
Customer Support
"""

# Classify the email
result = nlp(email_content)
print(result)