Fingerprinting a DDoS Attack

FNGERPRINTING A DD S ATTACK EFFECTIVE DISTILLATION IS THE KEY WHEN AN ATTACK TAKES PLACE: SCOTT'S Typical Automated Method Hundreds of millions of data points pour into a DDOS mitigation platform in real-time RAW DATA AUTO ANALYSIS Analyze data to detect anomalies and malicious traffic OUTCOME: Ineffective distillation Leads to murky results and an unclear fingerprint Use automated rules and human attack mitigation techniques to allow good traffic through and block Prolexic Human Mitigation Method Store billions of traffic and attack data metrics in the cloud bad traffic The Goal: • Make all incoming attack data useful to humans HUMAN MITIGATION (THE MISSING INGREDIENT) RAW DATA AUTO ANALYSIS The Problem: • There is a gap between what automated data analytics can do and what malicious attackers can do live behind their botnets Automatic decision making equipment is prone to false positives OUTCOME: Potent distillation This crucial extra step leads to clear and effective results with a highly identifiable fingerprint Conclusion: • That's why we need human DDOS mitigators CHEERS! D PROLEXIC COMPARE THESE 2 METHODS DDOS Attacks End Here.