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import pandas as pd
import random
import logging
from datetime import datetime, timedelta
# Configure logging
logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
# Generate random timestamps within the last 90 days
def random_timestamp():
start = datetime.now() - timedelta(days=90)
return start + timedelta(seconds=random.randint(0, 60 * 60 * 24 * 90))
# Generate random IP addresses
def random_ip():
return ".".join(str(random.randint(0, 255)) for _ in range(4))
# Define dataset attributes
protocols = ["TCP", "UDP", "ICMP"]
actions = ["Allow", "Deny"]
threat_levels = ["Low", "Medium", "High", "Critical"]
threat_types = ["DDoS", "Brute Force", "SQL Injection", "Port Scan", "Malware"]
response_actions = ["Blocked", "Alerted", "Monitored", "Escalated"]
# Generate dataset
data = {
"timestamp": [random_timestamp().strftime("%Y-%m-%d %H:%M:%S") for _ in range(500)],
"source_ip": [random_ip() for _ in range(500)],
"destination_ip": [random_ip() for _ in range(500)],
"protocol": [random.choice(protocols) for _ in range(500)],
"port": [random.randint(20, 65535) for _ in range(500)],
"action": [random.choice(actions) for _ in range(500)],
"threat_level": [random.choice(threat_levels) for _ in range(500)],
"threat_type": [random.choice(threat_types) for _ in range(500)],
"response_action": [random.choice(response_actions) for _ in range(500)],
}
# Convert to DataFrame
df = pd.DataFrame(data)
# Save as CSV with validation
output_file = "nsg_dataset.csv"
try:
df.to_csv(output_file, index=False)
logging.info(f"✅ NSG Dataset ({len(df)} records) saved to '{output_file}' successfully!")
except Exception as e:
logging.error(f"❌ Error saving dataset: {e}")
# Preview dataset
print(df.head())
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