Recognizing malicious software behaviors with tree automata inference

  • Authors:
  • Domagoj Babić;Daniel Reynaud;Dawn Song

  • Affiliations:
  • Computer Science Division, University of California, Berkeley, USA 94720-1776;Computer Science Division, University of California, Berkeley, USA 94720-1776;Computer Science Division, University of California, Berkeley, USA 94720-1776

  • Venue:
  • Formal Methods in System Design
  • Year:
  • 2012

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Abstract

We explore how formal methods and tools of the verification trade could be used for malware detection and analysis. In particular, we propose a new approach to learning and generalizing from observed malware behaviors based on tree automata inference. Our approach infers k-testable tree automata from system call dataflow dependency graphs. We show how inferred automata can be used for malware recognition and classification.