Motivated by applications in cybersecurity such as finding meaningful sequences of malware-related events buried inside large amounts of computer log data, we introduce the “planted path” problem and propose an algorithm to find fuzzy matchings between two trees. This algorithm can be used as a “building block” for more complicated workflows. We demonstrate usefulness of a few of such workflows in mining synthetically generated data as well as real-world ACME cybersecurity datasets.

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The Needle is a Thread: Finding Planted Paths in Noisy Process Trees

  • Maya Le,
  • Paweł Prałat,
  • Aaron Smith,
  • François Théberge

摘要

Motivated by applications in cybersecurity such as finding meaningful sequences of malware-related events buried inside large amounts of computer log data, we introduce the “planted path” problem and propose an algorithm to find fuzzy matchings between two trees. This algorithm can be used as a “building block” for more complicated workflows. We demonstrate usefulness of a few of such workflows in mining synthetically generated data as well as real-world ACME cybersecurity datasets.