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How to detect network anomalies based on traffic baseline?

Detecting network anomalies based on traffic baseline involves establishing a normal traffic pattern and identifying deviations from it. Here's how it works:

  1. Establish a Traffic Baseline:

    • Collect historical network traffic data over a period (e.g., daily, weekly) to define normal behavior.
    • Key metrics include bandwidth usage, packet rates, protocol distribution, and connection patterns.
  2. Define Thresholds:

    • Set acceptable ranges for each metric (e.g., average bandwidth ±10%).
    • Use statistical methods (mean, standard deviation) or machine learning to dynamic thresholds.
  3. Monitor Real-Time Traffic:

    • Continuously compare current traffic against the baseline.
    • Flag deviations exceeding thresholds as potential anomalies.
  4. Analyze and Respond:

    • Investigate flagged events (e.g., sudden traffic spikes, unusual protocols).
    • Correlate with logs or security tools to confirm threats (e.g., DDoS, data exfiltration).

Example:
A company’s baseline shows 1 Gbps peak bandwidth during business hours. If traffic suddenly jumps to 3 Gbps at 2 AM, it triggers an alert for investigation.

For scalable anomaly detection, Tencent Cloud offers Network Security Solutions like:

  • DDoS Protection: Detects and mitigates traffic anomalies.
  • Cloud Monitor: Tracks network metrics and sets custom alerts.
  • Tencent Cloud Network Intelligence: Uses AI to identify deviations in real time.