Detecting Malicious Traffic with Machine Learning

  1. Clustering data points within similar behavioral groups
  • High Data Density
  • Clear, Actionable Outcomes
  • Quantifiable Variation
Figure 1. We generate various groups with different behavior such as Inter-request time and the total number of unique endpoints (or URLs). Data points in each group exhibit similar behavior.
Figure 2. When we test a model, we apply the classifier to a new set of data. We want to answer the following questions: Did our model discover new clients that exhibit known bad behavior? Does our model detect requests by bots or valid users (humans)?

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Formerly Verizon Media Platform, Edgecast enables companies to deliver high performance, secure digital experiences at scale worldwide. https://edgecast.com/

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Edgecast

Edgecast

Formerly Verizon Media Platform, Edgecast enables companies to deliver high performance, secure digital experiences at scale worldwide. https://edgecast.com/

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