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Fingerprinting a DDoS Attack
 

Fingerprinting a DDoS Attack

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    Fingerprinting a DDoS Attack Fingerprinting a DDoS Attack Document Transcript

    • EFFECTIVE DISTILLATION IS THE KEY WHEN AN ATTACK TAKES PLACE: Hundreds of millions of data points pour into a DDoS mitigation platform in real-time ?? ??? ? ?? ? ? ? ? Analyze data to detect anomalies and malicious traffic Use automated rules and human attack mitigation techniques to allow good traffic through and block bad traffic The Goal: 101101010001010100011 010100110101001110011 101010011010101001100 101010100110010100101 101010010101010100101 010100101010011100010 101010100101001110101 Store billions of traffic and attack data metrics in the cloud • Make all incoming attack data useful to humans Typical Automated Method RAW DATA AUTO ANALYSIS OUTCOME: Ineffective distillation Leads to murky results and an unclear fingerprint Prolexic Human Mitigation Method 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 Conclusion: • That’s why we need human DDoS mitigators COMPARE THESE 2 METHODS HUMAN MITIGATION (THE MISSING INGREDIENT) OUTCOME: Potent distillation This crucial extra step leads to clear and effective results with a highly identifiable fingerprint CHEERS!