Advanced Analysis Techniques

Sophisticated investigations require advanced techniques:

Machine Learning Applications:

Anomaly detection
Behavioral analysis
Automated classification
Predictive analytics

Threat Hunting in Network Data:

# Detecting beaconing behavior
import pandas as pd
import numpy as np

def detect_beaconing(flows):
    # Group by source/destination pair
    grouped = flows.groupby(['src_ip', 'dst_ip', 'dst_port'])
    
    # Calculate time deltas
    for name, group in grouped:
        times = pd.to_datetime(group['timestamp'])
        deltas = times.diff().dt.total_seconds()
        
        # Check for regular intervals
        if deltas.std() < 5:  # Low standard deviation
            print(f"Potential beaconing: {name}")