Data Science with ML

C2C
  • Apply statistical modeling and data science techniques to transaction and TCP L4 telemetry to identify anomalous traffic and behavioral patterns.
  • Build behavioral baselines and anomaly detection models using time-series analysis, clustering, correlation, outlier detection, and statistical thresholds.
  • Engineer features from transaction, connection, velocity, retry, batch, and historical alert data to improve detection accuracy.
  • Develop statistical scoring and classification models to differentiate legitimate, duplicate, retry, anomalous, and potential DDoS activity.
  • Analyze historical incidents and alerts to optimize detection thresholds and reduce false positives.
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