This paper presents a framework for (1) generating variants of known attacks, (2) replaying attack variants in an isolated environment and, (3) validating detection capabilities of attack detection techniques against the variants. Our framework facilitates reproducible security experiments. We generated 648 variants of three real-world attacks (observed at the National Center for Supercomputing Applications at the University of Illinois). Our experiment showed the value of generating attack variants by quantifying the detection capabilities of three detection methods: a signature-based detection technique, an anomaly-based detection technique, and a probabilistic graphical model-based technique.

Original languageEnglish (US)
Number of pages10
StatePublished - 2016
EventSymposium and Bootcamp on the Science of Security, HotSos 2016 - Pittsburgh, United States
Duration: Apr 19 2016Apr 21 2016


ConferenceSymposium and Bootcamp on the Science of Security, HotSos 2016
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


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